Complete record

Publications

All publications, grouped by year. For a thematic view, see the research page. Also on Google Scholar.

Topic Type Year Selected only

2026

PhantomSeal: Proactive Deepfakes Defense with Identity/Context Protection and Forensic Tracing

Liangqin Ren, Zeyan Liu, Ye Wang, Yuxin Chen, Fengjun Li, Bo Luo

CCS 2026

bib

@inproceedings{ren2026phantomseal,
  keywords = {other},
  title = {PhantomSeal: Proactive Deepfakes Defense with Identity/Context Protection and Forensic Tracing},
  author = {Ren, Liangqin and Liu, Zeyan and Wang, Ye and Chen, Yuxin and Li, Fengjun and Luo, Bo},
  booktitle = {ACM SIGSAC Conference on Computer and Communications Security (CCS)},
  note_venue = {Hague, Netherlands},
  year = {2026},
  month = oct,
  venue = {CCS},
  topic = {applications}
}

Text-Twin-Translation: A Full-Stack Machine Learning Framework for Functional Material-Device Systems Discovery

Rui Ding, Zixin Ding, Rodrigo P. Ferreira, Yuxin Chen, Junhong Chen

KDD 2026

paper workshop

bib

@inproceedings{ding2026ttt,
  keywords = {ai-for-science},
  theme = {experiment-discovery},
  featured = {true},
  title = {Text-Twin-Translation: A Full-Stack Machine Learning Framework for Functional Material-Device Systems Discovery},
  author = {Ding, Rui and Ding, Zixin and Ferreira, Rodrigo P. and Chen, Yuxin and Chen, Junhong},
  booktitle = {ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)},
  note_venue = {AI for Sciences Track},
  year = {2026},
  month = aug,
  month_name = {August},
  prelim = {ICLR 2026 Workshop on AI for Accelerated Materials Design (AI4MAT-ICLR-2026), April 2026},
  prelim_url = {https://openreview.net/forum?id=eqBZpIAHGC},
  url = {https://dl.acm.org/doi/10.1145/3770855.3819013},
  venue = {KDD},
  topic = {ai4science},
  selected = {true}
}

Preliminary version: ICLR 2026 Workshop on AI for Accelerated Materials Design (AI4MAT-ICLR-2026), April 2026.

GPT-Driven Drug Optimization with Structured Policy Optimization Post-training

Xuefeng Liu, Songhao Jiang, Siyu Chen, Zhuoran Yang, Yuxin Chen, Ian T. Foster, Rick L. Stevens

MLHC 2026

bib

@inproceedings{liu2026gpt,
  keywords = {reinforcement-learning, ai-for-science},
  title = {GPT-Driven Drug Optimization with Structured Policy Optimization Post-training},
  author = {Liu, Xuefeng and Jiang, Songhao and Chen, Siyu and Yang, Zhuoran and Chen, Yuxin and Foster, Ian T. and Stevens, Rick L.},
  booktitle = {Conference on Machine Learning for Healthcare (MLHC)},
  year = {2026},
  month = aug,
  venue = {MLHC},
  topic = {ai4science}
}

Active Curriculum Refinement for Reinforcement Learning

Zhenya Liu, Yuxin Chen

ICML 2026

paper url project

bib

@inproceedings{liu2026curriculum,
  keywords = {reinforcement-learning, active-learning},
  area = {reinforcement-learning},
  title = {Active Curriculum Refinement for Reinforcement Learning},
  author = {Liu, Zhenya and Chen, Yuxin},
  booktitle = {International Conference on Machine Learning (ICML)},
  note_venue = {Seoul, South Korea},
  year = {2026},
  month = jul,
  month_name = {July},
  url = {https://openreview.net/forum?id=BhS108cyjT},
  link = {https://icml.cc/virtual/2026/poster/65627},
  website = {https://liu-zhenya.github.io/active-curriculum-refinement/},
  venue = {ICML},
  topic = {decision-making},
  selected = {true},
  summary = {Reinforcement-learning agents that actively refine the curriculum they learn from.}
}

Geometry, Not Energy Surface, Drives the Neutral MLIP-DFT Gap in Atomistic Interaction Surrogates

Rui Ding, Zixin Ding, Rodrigo P. Ferreira, Yuxin Chen, Junhong Chen

ICML AI4Physics 2026

paper

bib

@inproceedings{ding2026geometry,
  keywords = {ai-for-science},
  theme = {simulation-computation},
  selected = {true},
  title = {Geometry, Not Energy Surface, Drives the Neutral MLIP-DFT Gap in Atomistic Interaction Surrogates},
  author = {Ding, Rui and Ding, Zixin and Ferreira, Rodrigo P. and Chen, Yuxin and Chen, Junhong},
  booktitle = {AI4Physics: An ICML 2026 Workshop on AI for Physics},
  year = {2026},
  month = jul,
  month_name = {July},
  link = {https://icml.cc/virtual/2026/72573},
  venue = {ICML AI4Physics},
  topic = {ai4science}
}

Learning to Trigger: Reinforcement Learning at the Large Hadron Collider

Zixin Ding, Shaghayegh Emami, Giovanna Salvi, Cecilia Tosciri, Abhijith Gandrakota, Jennifer Ngadiuba, Nhan Tran, Christian Herwig, David W. Miller, Yuxin Chen

ICML AI4Physics 2026 Best Paper Award

paper press

bib

@inproceedings{ding2026trigger,
  keywords = {reinforcement-learning, ai-for-science},
  area = {scientific-discovery},
  press = {https://news.uchicago.edu/story/uchicago-led-team-builds-ai-data-filter-cerns-particle-collider},
  theme = {experiment-discovery},
  title = {Learning to Trigger: Reinforcement Learning at the Large Hadron Collider},
  author = {Ding, Zixin and Emami, Shaghayegh and Salvi, Giovanna and Tosciri, Cecilia and Gandrakota, Abhijith and Ngadiuba, Jennifer and Tran, Nhan and Herwig, Christian and Miller, David W. and Chen, Yuxin},
  booktitle = {AI4Physics: An ICML 2026 Workshop on AI for Physics},
  year = {2026},
  month = jul,
  month_name = {July},
  award = {Best Paper Award},
  link = {https://icml.cc/virtual/2026/72562},
  venue = {ICML AI4Physics},
  topic = {ai4science},
  selected = {true},
  summary = {First demonstration of RL-based trigger control on real Large Hadron Collider collision data.}
}

Automatic Prompt Engineering for Scalable Prompt Inversion in Text-to-Image Ad Generation

Zixin Ding, Qi Zeng, Boying Gong, Wenlong Deng, Bo Pan, Yuxin Chen

ACL 2026

paper

bib

@inproceedings{ding2026ape,
  keywords = {llm-data},
  title = {Automatic Prompt Engineering for Scalable Prompt Inversion in Text-to-Image Ad Generation},
  author = {Ding, Zixin and Zeng, Qi and Gong, Boying and Deng, Wenlong and Pan, Bo and Chen, Yuxin},
  booktitle = {Annual Meeting of the Association for Computational Linguistics (ACL) -- Industry Track},
  year = {2026},
  month = jul,
  month_name = {July},
  url = {https://openreview.net/pdf?id=oVQy58oEpX},
  venue = {ACL},
  topic = {data-scaling}
}

Scaling Textual Gradients via Sampling-Based Momentum

Zixin Ding, Junyuan Hong, Zhan Shi, Tianhao Wang, Zinan Lin, Li Yin, Meng Liu, Zhangyang Wang, Yuxin Chen

CAIS 2026

paper workshop

bib

@inproceedings{ding2026tsgdm,
  keywords = {llm-data},
  area = {emerging},
  title = {Scaling Textual Gradients via Sampling-Based Momentum},
  author = {Ding, Zixin and Hong, Junyuan and Shi, Zhan and Wang, Tianhao and Lin, Zinan and Yin, Li and Liu, Meng and Wang, Zhangyang and Chen, Yuxin},
  booktitle = {ACM Conference on AI and Agentic Systems (CAIS)},
  year = {2026},
  month = may,
  month_name = {May},
  prelim = {Second Workshop on Test-Time Adaptation: Putting Updates to the Test! at ICML (PUT), July 2025},
  prelim_url = {https://openreview.net/forum?id=Hd8KbY52FF},
  link = {https://www.caisconf.org/program/2026/papers/scaling-textual-gradients-via-sampling-based-momentum/},
  venue = {CAIS},
  topic = {data-scaling},
  selected = {true}
}

Preliminary version: Second Workshop on Test-Time Adaptation: Putting Updates to the Test! at ICML (PUT), July 2025.

Accelerating PDE Surrogates via RL-Guided Mesh Optimization

Yang Meng, Ruoxi Jiang, Zhuokai Zhao, Chong Liu, Rebecca Willett, Yuxin Chen

AISTATS 2026

paper

bib

@inproceedings{meng2026rlmesh,
  keywords = {reinforcement-learning, active-learning, ai-for-science},
  theme = {simulation-computation},
  title = {Accelerating PDE Surrogates via RL-Guided Mesh Optimization},
  author = {Meng, Yang and Jiang, Ruoxi and Zhao, Zhuokai and Liu, Chong and Willett, Rebecca and Chen, Yuxin},
  booktitle = {International Conference on Artificial Intelligence and Statistics (AISTATS)},
  year = {2026},
  month = may,
  month_name = {May},
  url = {https://arxiv.org/abs/2603.02066},
  venue = {AISTATS},
  topic = {ai4science},
  selected = {true},
  summary = {RL-guided mesh optimization adaptively allocates computation where it matters for PDE surrogate models.}
}

Scaling Laws Revisited: Modeling the Role of Data Quality in Language Model Pretraining

Anirudh Subramanyam, Yuxin Chen, Robert L. Grossman

ICLR 2026

paper

bib

@inproceedings{subramanyam2026scaling,
  keywords = {llm-data, learning-theory},
  area = {emerging},
  title = {Scaling Laws Revisited: Modeling the Role of Data Quality in Language Model Pretraining},
  author = {Subramanyam, Anirudh and Chen, Yuxin and Grossman, Robert L.},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  month = apr,
  month_name = {April},
  url = {https://openreview.net/forum?id=x54wwB6QvL},
  venue = {ICLR},
  topic = {data-scaling},
  selected = {true},
  summary = {How heterogeneous data quality changes the scaling behavior of language-model pretraining.}
}

Towards a Self-Driving Trigger at the LHC: Adaptive Response in Real Time

Shaghayegh Emami, Cecilia Tosciri, Giovanna Salvi, Zixin Ding, Yuxin Chen, Abhijith Gandrakota, Christian Herwig, David W. Miller, Jennifer Ngadiuba, Nhan Tran

MLST 2026

preprint

bib

@article{emami2026trigger,
  keywords = {ai-for-science},
  theme = {experiment-discovery},
  title = {Towards a Self-Driving Trigger at the LHC: Adaptive Response in Real Time},
  author = {Emami, Shaghayegh and Tosciri, Cecilia and Salvi, Giovanna and Ding, Zixin and Chen, Yuxin and Gandrakota, Abhijith and Herwig, Christian and Miller, David W. and Ngadiuba, Jennifer and Tran, Nhan},
  journal = {Machine Learning: Science and Technology},
  year = {2026},
  preprint = {https://arxiv.org/abs/2601.08910},
  venue = {MLST},
  topic = {ai4science},
  selected = {true}
}

2025

Formal Models of Active Learning from Contrastive Examples

Farnam Mansouri, Hans U. Simon, Adish Singla, Yuxin Chen, Sandra Zilles

NeurIPS 2025

paper

bib

@inproceedings{mansouri2025formal,
  keywords = {active-learning, learning-theory},
  title = {Formal Models of Active Learning from Contrastive Examples},
  author = {Mansouri, Farnam and Simon, Hans U. and Singla, Adish and Chen, Yuxin and Zilles, Sandra},
  booktitle = {Conference on Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  month = dec,
  month_name = {December},
  url = {https://openreview.net/pdf?id=AQ21krZgax},
  venue = {NeurIPS},
  topic = {adaptive-learning},
  selected = {true}
}

Deep Research with Local-Web RAG: Toward Automated System-Level Materials Discovery

Rui Ding, Rodrigo P. Ferreira, Yuxin Chen, Junhong Chen

NeurIPS AI4Mat 2025

paper

bib

@inproceedings{ding2025deepresearch,
  keywords = {ai-for-science, llm-data},
  title = {Deep Research with Local-Web RAG: Toward Automated System-Level Materials Discovery},
  author = {Ding, Rui and Ferreira, Rodrigo P. and Chen, Yuxin and Chen, Junhong},
  booktitle = {NeurIPS 2025 Workshop on AI for Accelerated Materials Discovery (AI4Mat)},
  year = {2025},
  month = dec,
  month_name = {December},
  url = {https://arxiv.org/abs/2511.18303},
  venue = {NeurIPS AI4Mat},
  topic = {ai4science}
}

A Self-driving Physical Vapor Deposition System Making Sample-specific Decisions on the Fly

Yuanlong Bill Zheng, Connor Blake, Layla Mravac, Fengxue Zhang, Yuxin Chen, Shuolong Yang

npj Comput. Mater. 2025

paper press

bib

@article{zheng2025pvd,
  keywords = {ai-for-science},
  area = {scientific-discovery},
  theme = {experiment-discovery},
  press = {https://pme.uchicago.edu/news-events/news/self-driving-lab-learns-grow-materials-its-own},
  title = {A Self-driving Physical Vapor Deposition System Making Sample-specific Decisions on the Fly},
  author = {Zheng, Yuanlong Bill and Blake, Connor and Mravac, Layla and Zhang, Fengxue and Chen, Yuxin and Yang, Shuolong},
  journal = {npj Computational Materials},
  year = {2025},
  month = nov,
  month_name = {November},
  url = {https://www.nature.com/articles/s41524-025-01805-0},
  venue = {npj Comput. Mater.},
  topic = {ai4science},
  selected = {true},
  summary = {An autonomous thin-film deposition system that makes sample-specific experimental decisions in real time.}
}

Real-Time Phosphate Monitoring via Plant-Derived Graphene Ink FET Sensors Integrated with Deep Learning

Rapti Ghosh, Fengxue Zhang, Hyun-June Jang, Janan Hui, Kayla Vittore, Haoyang You, Rozyyev Vepa, Wen Zhuang, Xingkang Huang, Haihui Pu, Jeffrey W. Elam, Stuart J. Rowan, DoKyoung Lee, Elizabeth A. Ainsworth, Mark C. Hersam, Yuxin Chen, Junhong Chen

EEM 2025

paper

bib

@article{ghosh2025phosphate,
  keywords = {ai-for-science},
  title = {Real-Time Phosphate Monitoring via Plant-Derived Graphene Ink FET Sensors Integrated with Deep Learning},
  author = {Ghosh, Rapti and Zhang, Fengxue and Jang, Hyun-June and Hui, Janan and Vittore, Kayla and You, Haoyang and Vepa, Rozyyev and Zhuang, Wen and Huang, Xingkang and Pu, Haihui and Elam, Jeffrey W. and Rowan, Stuart J. and Lee, DoKyoung and Ainsworth, Elizabeth A. and Hersam, Mark C. and Chen, Yuxin and Chen, Junhong},
  journal = {Energy \& Environmental Materials},
  year = {2025},
  month = sep,
  month_name = {September},
  url = {https://onlinelibrary.wiley.com/doi/full/10.1002/eem2.70144},
  venue = {EEM},
  topic = {ai4science}
}

Direct Regret Optimization in Bayesian Optimization

Fengxue Zhang, Yuxin Chen

ICML ExAI 2025

paper preprint

bib

@inproceedings{zhang2025dro,
  keywords = {bayesian-optimization, active-learning, representation-learning},
  area = {bayesian-optimization},
  featured = {true},
  title = {Direct Regret Optimization in Bayesian Optimization},
  author = {Zhang, Fengxue and Chen, Yuxin},
  booktitle = {Exploration in AI Today Workshop at ICML (ExAI)},
  year = {2025},
  month = jul,
  month_name = {July},
  url = {https://openreview.net/forum?id=Vk6qlff6Qb},
  preprint = {https://arxiv.org/abs/2507.06529},
  venue = {ICML ExAI},
  topic = {decision-making},
  selected = {true}
}

Active Advantage-Aligned Online Reinforcement Learning with Offline Data

Xuefeng Liu, Hung T. C. Le, Siyu Chen, Rick Stevens, Zhuoran Yang, Matthew Walter, Yuxin Chen

ICML ExAI 2025

paper

bib

@inproceedings{liu2025a3rl,
  keywords = {reinforcement-learning},
  title = {Active Advantage-Aligned Online Reinforcement Learning with Offline Data},
  author = {Liu, Xuefeng and Le, Hung T. C. and Chen, Siyu and Stevens, Rick and Yang, Zhuoran and Walter, Matthew and Chen, Yuxin},
  booktitle = {Exploration in AI Today Workshop at ICML (ExAI)},
  year = {2025},
  month = jul,
  month_name = {July},
  url = {https://openreview.net/forum?id=Yc0GAtiZzg},
  venue = {ICML ExAI},
  topic = {decision-making}
}

Finding Interior Optimum of Black-box Constrained Objective with Bayesian Optimization

Fengxue Zhang, Yuxin Chen

UAI 2025

paper

bib

@inproceedings{zhang2025interior,
  keywords = {bayesian-optimization},
  title = {Finding Interior Optimum of Black-box Constrained Objective with Bayesian Optimization},
  author = {Zhang, Fengxue and Chen, Yuxin},
  booktitle = {Conference on Uncertainty in Artificial Intelligence (UAI)},
  year = {2025},
  month = jul,
  month_name = {July},
  url = {https://openreview.net/forum?id=0kW2LHEx7z},
  prelim = {NeurIPS Workshop on Bayesian Decision-making and Uncertainty (BDU), December 2024},
  venue = {UAI},
  topic = {decision-making}
}

Preliminary version: NeurIPS Workshop on Bayesian Decision-making and Uncertainty (BDU), December 2024.

Bayesian Optimization with Inexact Acquisition: Is Random Grid Search Sufficient?

Hwanwoo Kim, Chong Liu, Yuxin Chen

UAI 2025

paper

bib

@inproceedings{kim2025inexact,
  keywords = {bayesian-optimization},
  title = {Bayesian Optimization with Inexact Acquisition: Is Random Grid Search Sufficient?},
  author = {Kim, Hwanwoo and Liu, Chong and Chen, Yuxin},
  booktitle = {Conference on Uncertainty in Artificial Intelligence (UAI)},
  year = {2025},
  month = jul,
  month_name = {July},
  url = {https://openreview.net/forum?id=d1zqR0eqSR},
  venue = {UAI},
  topic = {decision-making}
}

Constrained Multi-objective Bayesian Optimization

Diantong Li, Fengxue Zhang, Chong Liu, Yuxin Chen

AISTATS 2025

paper workshop

bib

@inproceedings{li2025cmobo,
  keywords = {bayesian-optimization},
  title = {Constrained Multi-objective Bayesian Optimization},
  author = {Li, Diantong and Zhang, Fengxue and Liu, Chong and Chen, Yuxin},
  booktitle = {International Conference on Artificial Intelligence and Statistics (AISTATS)},
  year = {2025},
  month = may,
  month_name = {May},
  url = {https://proceedings.mlr.press/v258/li25a.html},
  prelim = {NeurIPS Workshop on Bayesian Decision-making and Uncertainty (BDU), December 2024},
  prelim_url = {https://openreview.net/forum?id=lHnbPVKbts},
  venue = {AISTATS},
  topic = {decision-making},
  selected = {true}
}

Preliminary version: NeurIPS Workshop on Bayesian Decision-making and Uncertainty (BDU), December 2024.

Robust Multi-fidelity Bayesian Optimization with Deep Kernel and Partition

Fengxue Zhang, Thomas Desautels, Yuxin Chen

AISTATS 2025

paper workshop

bib

@inproceedings{zhang2025rmfbo,
  keywords = {bayesian-optimization, representation-learning},
  title = {Robust Multi-fidelity Bayesian Optimization with Deep Kernel and Partition},
  author = {Zhang, Fengxue and Desautels, Thomas and Chen, Yuxin},
  booktitle = {International Conference on Artificial Intelligence and Statistics (AISTATS)},
  year = {2025},
  month = may,
  month_name = {May},
  url = {https://proceedings.mlr.press/v258/zhang25g.html},
  prelim = {NeurIPS Workshop on Bayesian Decision-making and Uncertainty (BDU), December 2024},
  prelim_url = {https://openreview.net/forum?id=FTDDW41M5m},
  venue = {AISTATS},
  topic = {decision-making}
}

Preliminary version: NeurIPS Workshop on Bayesian Decision-making and Uncertainty (BDU), December 2024.

Leveraging Data Mining, Active Learning, and Domain Adaptation in a Multi-Stage, Machine Learning-Driven Approach for the Efficient Discovery of Advanced Acidic Oxygen Evolution Electrocatalysts

Rui Ding, Jianguo Liu, Kang Hua, Xuebin Wang, Xiaoben Zhang, Minhua Shao, Yuxin Chen, Junhong Chen

Sci. Adv. 2025

paper preprint

bib

@article{ding2025oer,
  keywords = {ai-for-science, active-learning},
  area = {scientific-discovery},
  theme = {experiment-discovery},
  title = {Leveraging Data Mining, Active Learning, and Domain Adaptation in a Multi-Stage, Machine Learning-Driven Approach for the Efficient Discovery of Advanced Acidic Oxygen Evolution Electrocatalysts},
  author = {Ding, Rui and Liu, Jianguo and Hua, Kang and Wang, Xuebin and Zhang, Xiaoben and Shao, Minhua and Chen, Yuxin and Chen, Junhong},
  journal = {Science Advances},
  year = {2025},
  month = apr,
  month_name = {April},
  url = {https://www.science.org/doi/10.1126/sciadv.adr9038},
  preprint = {https://arxiv.org/abs/2407.04877},
  venue = {Sci. Adv.},
  topic = {ai4science},
  selected = {true}
}

Expediting Field-Effect Transistor Chemical Sensor Design with Neuromorphic Spiking Graph Neural Networks

Rodrigo P. Ferreira, Rui Ding, Fengxue Zhang, Haihui Pu, Claire Donnat, Yuxin Chen, Junhong Chen

MSDE 2025 Selected as MSDE Recent HOT Article

paper press

bib

@article{ferreira2025sgnn,
  keywords = {ai-for-science},
  title = {Expediting Field-Effect Transistor Chemical Sensor Design with Neuromorphic Spiking Graph Neural Networks},
  author = {Ferreira, Rodrigo P. and Ding, Rui and Zhang, Fengxue and Pu, Haihui and Donnat, Claire and Chen, Yuxin and Chen, Junhong},
  journal = {Molecular Systems Design \& Engineering (MSDE)},
  year = {2025},
  month = mar,
  month_name = {March},
  award = {Selected as MSDE Recent HOT Article},
  press = {https://pme.uchicago.edu/news-events/news/ai-helps-scientists-design-better-sensors-pollutants-and-beyond},
  link = {https://pubs.rsc.org/en/content/articlelanding/2025/me/d4me00203b},
  venue = {MSDE},
  topic = {ai4science}
}

2024

Contextual Active Model Selection

Xuefeng Liu, Fangfang Xia, Rick L. Stevens, Yuxin Chen

NeurIPS 2024

paper poster

bib

@inproceedings{liu2024cams,
  keywords = {active-learning, learning-theory},
  title = {Contextual Active Model Selection},
  author = {Liu, Xuefeng and Xia, Fangfang and Stevens, Rick L. and Chen, Yuxin},
  booktitle = {Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  month = dec,
  month_name = {December},
  url = {https://openreview.net/forum?id=ZizwgYErtQ},
  prelim = {ICML Workshop on Adaptive Experimental Design and Active Learning in the Real World (ReALML), July 2022},
  poster = {/files/papers/liu22cams-poster.pdf},
  venue = {NeurIPS},
  topic = {adaptive-learning},
  selected = {true}
}

Preliminary version: ICML Workshop on Adaptive Experimental Design and Active Learning in the Real World (ReALML), July 2022.

Active Learning for Optimal Minimization of Experimental Characterization Uncertainty

Marcus Schwarting, Nathan Seifert, Logan Ward, Ben Blaiszik, Ian Foster, Yuxin Chen, Kirill Prozument

NeurIPS BDU 2024

paper

bib

@inproceedings{schwarting2024alchar,
  keywords = {ai-for-science, active-learning},
  title = {Active Learning for Optimal Minimization of Experimental Characterization Uncertainty},
  author = {Schwarting, Marcus and Seifert, Nathan and Ward, Logan and Blaiszik, Ben and Foster, Ian and Chen, Yuxin and Prozument, Kirill},
  booktitle = {NeurIPS Workshop on Bayesian Decision-making and Uncertainty (BDU)},
  year = {2024},
  month = dec,
  month_name = {December},
  url = {https://openreview.net/forum?id=0EjE4hhI1U},
  venue = {NeurIPS BDU},
  topic = {ai4science}
}

Direct Acquisition Optimization for Low-Budget Active Learning

Zhuokai Zhao, Yibo Jiang, Yuxin Chen

NeurIPS BDU 2024 Lightning talk

paper

bib

@inproceedings{zhao2024dao,
  keywords = {active-learning, representation-learning},
  title = {Direct Acquisition Optimization for Low-Budget Active Learning},
  author = {Zhao, Zhuokai and Jiang, Yibo and Chen, Yuxin},
  booktitle = {NeurIPS Workshop on Bayesian Decision-making and Uncertainty (BDU)},
  year = {2024},
  month = dec,
  month_name = {December},
  award = {Lightning talk},
  url = {https://openreview.net/forum?id=ODjjSqlH8j},
  venue = {NeurIPS BDU},
  topic = {adaptive-learning}
}

Reasoning in Reasoning: A Hierarchical Framework for Better and Faster Neural Theorem Proving

Ziyu Ye, Jiacheng Chen, Jonathan Light, Yifei Wang, Jiankai Sun, Mac Schwager, Philip Torr, Guohao Li, Yuxin Chen, Kaiyu Yang, Yisong Yue, Ziniu Hu

NeurIPS Math-AI 2024

paper

bib

@inproceedings{ye2024rir,
  keywords = {llm-data},
  title = {Reasoning in Reasoning: A Hierarchical Framework for Better and Faster Neural Theorem Proving},
  author = {Ye, Ziyu and Chen, Jiacheng and Light, Jonathan and Wang, Yifei and Sun, Jiankai and Schwager, Mac and Torr, Philip and Li, Guohao and Chen, Yuxin and Yang, Kaiyu and Yue, Yisong and Hu, Ziniu},
  booktitle = {NeurIPS Workshop on Mathematical Reasoning and AI (Math-AI)},
  year = {2024},
  month = dec,
  month_name = {December},
  url = {https://openreview.net/forum?id=H5hePMXKht},
  venue = {NeurIPS Math-AI},
  topic = {data-scaling}
}

Unlocking the Potential: Machine Learning Applications in Electrocatalyst Design for Electrochemical Hydrogen Energy Transformation

Rui Ding, Junhong Chen, Yuxin Chen, Jianguo Liu, Yoshio Bando, Xuebin Wang

Chem. Soc. Rev. 2024 Featured as inside front cover

paper press

bib

@article{ding2024review,
  keywords = {ai-for-science},
  title = {Unlocking the Potential: Machine Learning Applications in Electrocatalyst Design for Electrochemical Hydrogen Energy Transformation},
  author = {Ding, Rui and Chen, Junhong and Chen, Yuxin and Liu, Jianguo and Bando, Yoshio and Wang, Xuebin},
  journal = {Chemical Society Reviews},
  year = {2024},
  month = dec,
  month_name = {December},
  award = {Featured as inside front cover},
  press = {https://pme.uchicago.edu/news-events/news/machine-learning-techniques-discover-new-materials-hydrogen-energy},
  link = {https://pubs.rsc.org/en/content/articlehtml/2024/cs/d4cs00844h},
  venue = {Chem. Soc. Rev.},
  topic = {ai4science}
}

A Sustainable Manufacturing Paradigm to Address Grand Challenges in Sustainability and Climate Change

Haihui Pu, Jinrui Zhang, Chao Liang, Mark C. Hersam, Stuart J. Rowan, Wei Chen, Santanu Chaudhuri, Elizabeth A. Ainsworth, DoKyoung Lee, Jonathan Claussen, Yuxin Chen, Rebecca Willett, Jennifer B. Dunn, Junhong Chen

ACS SRM 2024

paper

bib

@article{pu2024sustainable,
  keywords = {ai-for-science},
  title = {A Sustainable Manufacturing Paradigm to Address Grand Challenges in Sustainability and Climate Change},
  author = {Pu, Haihui and Zhang, Jinrui and Liang, Chao and Hersam, Mark C. and Rowan, Stuart J. and Chen, Wei and Chaudhuri, Santanu and Ainsworth, Elizabeth A. and Lee, DoKyoung and Claussen, Jonathan and Chen, Yuxin and Willett, Rebecca and Dunn, Jennifer B. and Chen, Junhong},
  journal = {ACS Sustainable Resource Management},
  year = {2024},
  month = nov,
  month_name = {November},
  link = {https://pubs.acs.org/doi/full/10.1021/acssusresmgt.4c00361},
  venue = {ACS SRM},
  topic = {ai4science}
}

No-Regret Learning of Nash Equilibrium for Black-Box Games via Gaussian Processes

Minbiao Han*, Fengxue Zhang*, Yuxin Chen

UAI 2024

paper poster

bib

@inproceedings{han2024nash,
  keywords = {bayesian-optimization, learning-theory},
  title = {No-Regret Learning of Nash Equilibrium for Black-Box Games via Gaussian Processes},
  author = {Han*, Minbiao and Zhang*, Fengxue and Chen, Yuxin},
  booktitle = {Conference on Uncertainty in Artificial Intelligence (UAI)},
  year = {2024},
  month = jul,
  month_name = {July},
  url = {https://arxiv.org/abs/2405.08318},
  poster = {/files/papers/han24-arise-uai24-poster.pdf},
  venue = {UAI},
  topic = {decision-making}
}

Learning to Rank for Active Learning via Multi-Task Bilevel Optimization

Zixin Ding, Si Chen, Ruoxi Jia, Yuxin Chen

UAI 2024

paper poster DMLR poster

bib

@inproceedings{ding2024rambo,
  keywords = {active-learning, representation-learning},
  area = {active-learning},
  title = {Learning to Rank for Active Learning via Multi-Task Bilevel Optimization},
  author = {Ding, Zixin and Chen, Si and Jia, Ruoxi and Chen, Yuxin},
  booktitle = {Conference on Uncertainty in Artificial Intelligence (UAI)},
  year = {2024},
  month = jul,
  month_name = {July},
  url = {http://arxiv.org/abs/2310.17044},
  poster = {/files/papers/ding24-rambo-uai24-poster.pdf},
  extra_links = {DMLR poster},
  venue = {UAI},
  topic = {adaptive-learning}
}

Model-based Policy Optimization under Approximate Bayesian Inference

Chaoqi Wang, Yuxin Chen, Kevin Murphy

AISTATS 2024 Oral presentation

paper project

bib

@inproceedings{wang2024mbpo,
  keywords = {reinforcement-learning, learning-theory},
  area = {reinforcement-learning},
  title = {Model-based Policy Optimization under Approximate Bayesian Inference},
  author = {Wang, Chaoqi and Chen, Yuxin and Murphy, Kevin},
  booktitle = {International Conference on Artificial Intelligence and Statistics (AISTATS)},
  year = {2024},
  month = may,
  month_name = {May},
  award = {Oral presentation},
  url = {https://proceedings.mlr.press/v238/wang24g/wang24g.pdf},
  website = {https://alecwangcq.github.io/pages/ps-mbpo/index.html},
  prelim = {ICML Workshop on New Frontiers in Learning, Control, and Dynamical Systems, 2023},
  venue = {AISTATS},
  topic = {decision-making}
}

Preliminary version: ICML Workshop on New Frontiers in Learning, Control, and Dynamical Systems, 2023.

Don’t Be Pessimistic Too Early: Look K Steps Ahead!

Chaoqi Wang, Ziyu Ye, Kevin Murphy, Yuxin Chen

AISTATS 2024

paper

bib

@inproceedings{wang2024pessimism,
  keywords = {reinforcement-learning, learning-theory},
  title = {Don't Be Pessimistic Too Early: Look K Steps Ahead!},
  author = {Wang, Chaoqi and Ye, Ziyu and Murphy, Kevin and Chen, Yuxin},
  booktitle = {International Conference on Artificial Intelligence and Statistics (AISTATS)},
  year = {2024},
  month = may,
  month_name = {May},
  url = {https://proceedings.mlr.press/v238/wang24h/wang24h.pdf},
  venue = {AISTATS},
  topic = {decision-making}
}

Blending Imitation and Reinforcement Learning for Robust Policy Improvement

Xuefeng Liu, Takuma Yoneda, Rick Stevens, Matthew Walter, Yuxin Chen

ICLR 2024 Spotlight presentation

paper project

bib

@inproceedings{liu2024rpi,
  keywords = {reinforcement-learning, learning-theory},
  area = {reinforcement-learning},
  title = {Blending Imitation and Reinforcement Learning for Robust Policy Improvement},
  author = {Liu, Xuefeng and Yoneda, Takuma and Stevens, Rick and Walter, Matthew and Chen, Yuxin},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  month = may,
  month_name = {May},
  award = {Spotlight presentation},
  url = {https://arxiv.org/abs/2310.01737},
  website = {https://robust-policy-improvement.github.io},
  venue = {ICLR},
  topic = {decision-making},
  selected = {true},
  summary = {Robust policy improvement by adaptively blending imitation and reinforcement learning.}
}

Beyond Reverse KL: Generalizing Direct Preference Optimization with Diverse Divergence Constraints

Chaoqi Wang, Yibo Jiang, Chenghao Yang, Han Liu, Yuxin Chen

ICLR 2024 Spotlight presentation

paper code poster

bib

@inproceedings{wang2024beyondrkl,
  keywords = {llm-data},
  featured = {true},
  title = {Beyond Reverse KL: Generalizing Direct Preference Optimization with Diverse Divergence Constraints},
  author = {Wang, Chaoqi and Jiang, Yibo and Yang, Chenghao and Liu, Han and Chen, Yuxin},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  month = may,
  month_name = {May},
  award = {Spotlight presentation},
  url = {https://arxiv.org/abs/2309.16240},
  poster = {/files/papers/wang24beyondRKL-iclr24-poster.png},
  code = {https://github.com/alecwangcq/f-divergence-dpo},
  prelim = {NeurIPS Workshop on Socially Responsible Language Modelling Research, December 2023},
  venue = {ICLR},
  topic = {data-scaling},
  selected = {true}
}

Preliminary version: NeurIPS Workshop on Socially Responsible Language Modelling Research, December 2023.

Enhancing Instance-Level Image Classification with Set-Level Labels

Renyu Zhang, Aly A. Khan, Yuxin Chen, Robert L. Grossman

ICLR 2024

paper poster

bib

@inproceedings{zhang2024facile,
  keywords = {active-learning, representation-learning, learning-theory},
  title = {Enhancing Instance-Level Image Classification with Set-Level Labels},
  author = {Zhang, Renyu and Khan, Aly A. and Chen, Yuxin and Grossman, Robert L.},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  month = may,
  month_name = {May},
  url = {https://arxiv.org/abs/2311.05659},
  poster = {/files/papers/zhang24facile-iclr24-poster.pdf},
  prelim = {Medical Imaging meets NeurIPS Workshop, December 2023},
  venue = {ICLR},
  topic = {adaptive-learning}
}

Preliminary version: Medical Imaging meets NeurIPS Workshop, December 2023.

2023

Efficient Online Decision Tree Learning with Active Feature Acquisition

Arman Rahbar, Ziyu Ye, Yuxin Chen, Morteza Haghir Chehreghani

IJCAI 2023

paper

bib

@inproceedings{rahbar2023dt,
  keywords = {active-learning},
  title = {Efficient Online Decision Tree Learning with Active Feature Acquisition},
  author = {Rahbar, Arman and Ye, Ziyu and Chen, Yuxin and Chehreghani, Morteza Haghir},
  booktitle = {International Joint Conference on Artificial Intelligence (IJCAI)},
  note_venue = {Macau},
  year = {2023},
  month = aug,
  month_name = {August},
  url = {https://arxiv.org/abs/2305.02093},
  venue = {IJCAI},
  topic = {adaptive-learning}
}

Active Policy Improvement from Multiple Black-box Oracles

Xuefeng Liu, Takuma Yoneda, Chaoqi Wang, Matthew Walter, Yuxin Chen

ICML 2023

paper code poster

bib

@inproceedings{liu2023maps,
  keywords = {reinforcement-learning, learning-theory},
  featured = {true},
  title = {Active Policy Improvement from Multiple Black-box Oracles},
  author = {Liu, Xuefeng and Yoneda, Takuma and Wang, Chaoqi and Walter, Matthew and Chen, Yuxin},
  booktitle = {International Conference on Machine Learning (ICML)},
  note_venue = {Hawaii},
  year = {2023},
  month = jul,
  month_name = {July},
  url = {https://proceedings.mlr.press/v202/liu23av/liu23av.pdf},
  poster = {/files/papers/liu23rpi-icml23-poster.pdf},
  code = {https://github.com/ripl/maps},
  venue = {ICML},
  topic = {decision-making}
}

Learning Region of Interest for Bayesian Optimization with Adaptive Level-Set Estimation

Fengxue Zhang, Jialin Song, James Bowden, Alexander Ladd, Yisong Yue, Thomas Desautels, Yuxin Chen

ICML 2023

paper

bib

@inproceedings{zhang2023ballet,
  keywords = {bayesian-optimization, representation-learning, learning-theory},
  area = {bayesian-optimization},
  featured = {true},
  title = {Learning Region of Interest for Bayesian Optimization with Adaptive Level-Set Estimation},
  author = {Zhang, Fengxue and Song, Jialin and Bowden, James and Ladd, Alexander and Yue, Yisong and Desautels, Thomas and Chen, Yuxin},
  booktitle = {International Conference on Machine Learning (ICML)},
  note_venue = {Hawaii},
  year = {2023},
  month = jul,
  month_name = {July},
  url = {https://arxiv.org/abs/2307.13371},
  venue = {ICML},
  topic = {decision-making},
  selected = {true}
}

Iterative Machine Teaching for Black-box Markov Learners

Chaoqi Wang, Sandra Zilles, Adish Singla, Yuxin Chen

ICML ToM 2023

paper

bib

@inproceedings{wang2023tom,
  keywords = {active-learning, learning-theory},
  title = {Iterative Machine Teaching for Black-box Markov Learners},
  author = {Wang, Chaoqi and Zilles, Sandra and Singla, Adish and Chen, Yuxin},
  booktitle = {ICML Workshop on Theory of Mind (ToM)},
  year = {2023},
  month = jul,
  url = {https://openreview.net/pdf?id=cmuVJMRWEK},
  venue = {ICML ToM},
  topic = {adaptive-learning}
}

Scalable Batch-Mode Deep Bayesian Active Learning via Equivalence Class Annealing

Renyu Zhang, Aly A. Khan, Robert L. Grossman, Yuxin Chen

ICLR 2023

paper poster

bib

@inproceedings{zhang2023balance,
  keywords = {active-learning},
  title = {Scalable Batch-Mode Deep Bayesian Active Learning via Equivalence Class Annealing},
  author = {Zhang, Renyu and Khan, Aly A. and Grossman, Robert L. and Chen, Yuxin},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2023},
  month = may,
  month_name = {May},
  url = {https://openreview.net/forum?id=GRZtigJljLY},
  poster = {/files/papers/zhang23balance-iclr23-poster.pdf},
  venue = {ICLR},
  topic = {adaptive-learning},
  selected = {true}
}

Learning Human-Compatible Representations for Case-Based Decision Support

Han Liu, Yizhou Tian, Chacha Chen, Shi Feng, Yuxin Chen, Chenhao Tan

ICLR 2023

paper

bib

@inproceedings{liu2023hcr,
  keywords = {representation-learning},
  title = {Learning Human-Compatible Representations for Case-Based Decision Support},
  author = {Liu, Han and Tian, Yizhou and Chen, Chacha and Feng, Shi and Chen, Yuxin and Tan, Chenhao},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2023},
  month = may,
  month_name = {May},
  url = {https://openreview.net/forum?id=r0xte-t40I},
  venue = {ICLR},
  topic = {adaptive-learning}
}

Online Learning of Energy Consumption for Navigation of Electric Vehicles

Niklas Åkerblom, Yuxin Chen, Morteza Haghir Chehreghani

AIJ 2023

paper

bib

@article{akerblom2023aij,
  keywords = {reinforcement-learning},
  title = {Online Learning of Energy Consumption for Navigation of Electric Vehicles},
  author = {Åkerblom, Niklas and Chen, Yuxin and Chehreghani, Morteza Haghir},
  journal = {Journal of Artificial Intelligence (AIJ)},
  note_venue = {extended version of the IJCAI'20 paper},
  year = {2023},
  url = {https://arxiv.org/abs/2111.02314},
  venue = {AIJ},
  topic = {decision-making}
}

2022

Trip Prediction by Leveraging Trip Histories from Neighboring Users

Yuxin Chen, Morteza Haghir Chehreghani

ITSC 2022

paper

bib

@inproceedings{chen2022trip,
  keywords = {other},
  title = {Trip Prediction by Leveraging Trip Histories from Neighboring Users},
  author = {Chen, Yuxin and Chehreghani, Morteza Haghir},
  booktitle = {IEEE International Conference on Intelligent Transportation Systems (ITSC)},
  year = {2022},
  month = oct,
  month_name = {October},
  url = {/files/papers/chen22triprec.pdf},
  venue = {ITSC},
  topic = {applications}
}

Explaining Why: How Instructions and User Interfaces Impact Annotator Rationales When Labeling Text Data

Jamar L. Sullivan Jr., Will Brackenbury, Andrew McNutt, Kevin Bryson, Kwam Byll, Yuxin Chen, Michael L. Littman, Chenhao Tan, Blase Ur

NAACL 2022

paper code

bib

@inproceedings{sullivan2022explaining,
  keywords = {active-learning},
  title = {Explaining Why: How Instructions and User Interfaces Impact Annotator Rationales When Labeling Text Data},
  author = {Jr., Jamar L. Sullivan and Brackenbury, Will and McNutt, Andrew and Bryson, Kevin and Byll, Kwam and Chen, Yuxin and Littman, Michael L. and Tan, Chenhao and Ur, Blase},
  booktitle = {North American Chapter of the Association for Computational Linguistics (NAACL)},
  year = {2022},
  month = jul,
  month_name = {July},
  url = {https://aclanthology.org/2022.naacl-main.38/},
  code = {https://aclanthology.org/attachments/2022.naacl-main.38.software.zip},
  venue = {NAACL},
  topic = {adaptive-learning}
}

Contextual Active Online Model Selection with Expert Advice

Xuefeng Liu, Fangfang Xia, Rick L. Stevens, Yuxin Chen

ICML ReALML 2022

paper poster

bib

@inproceedings{liu2022cams,
  keywords = {active-learning},
  title = {Contextual Active Online Model Selection with Expert Advice},
  author = {Liu, Xuefeng and Xia, Fangfang and Stevens, Rick L. and Chen, Yuxin},
  booktitle = {ICML Workshop on Adaptive Experimental Design and Active Learning in the Real World (ReALML)},
  year = {2022},
  month = jul,
  month_name = {July},
  url = {https://arxiv.org/abs/2207.06030},
  poster = {/files/papers/liu22cams-poster.pdf},
  venue = {ICML ReALML},
  topic = {adaptive-learning}
}

The Price of Sparsity: Generalization and Memorization in Sparse Neural Network

Ziyu Ye, Chaoqi Wang, Zixin Ding, Yuxin Chen

SNN 2022

paper poster

bib

@inproceedings{ye2022sparsity,
  keywords = {llm-data},
  title = {The Price of Sparsity: Generalization and Memorization in Sparse Neural Network},
  author = {Ye, Ziyu and Wang, Chaoqi and Ding, Zixin and Chen, Yuxin},
  booktitle = {Sparsity in Neural Networks Workshop (SNN)},
  year = {2022},
  month = jul,
  month_name = {July},
  url = {https://github.com/ZIYU-DEEP/Generalization-and-Memorization-in-Sparse-Training},
  poster = {/files/papers/ye22snn-poster.pdf},
  venue = {SNN},
  topic = {data-scaling}
}

Class-wise Thresholding for Detecting Out-of-Distribution Data

Matteo Guarrera, Baihong Jin, Tung-Wei Lin, Maria Zuluaga, Yuxin Chen, Alberto Sangiovanni-Vincentelli

CVPR TCV 2022

paper

bib

@inproceedings{guarrera2022classwise,
  keywords = {other},
  title = {Class-wise Thresholding for Detecting Out-of-Distribution Data},
  author = {Guarrera, Matteo and Jin, Baihong and Lin, Tung-Wei and Zuluaga, Maria and Chen, Yuxin and Sangiovanni-Vincentelli, Alberto},
  booktitle = {CVPR Workshop on Fair, Data-Efficient, and Trusted Computer Vision (TCV)},
  year = {2022},
  month = jun,
  month_name = {June},
  url = {https://arxiv.org/abs/2110.15292},
  venue = {CVPR TCV},
  topic = {applications}
}

2021

Teaching an Active Learner with Contrastive Examples

Chaoqi Wang, Adish Singla, Yuxin Chen

NeurIPS 2021

paper

bib

@inproceedings{wang2021contrastive,
  keywords = {active-learning, learning-theory},
  title = {Teaching an Active Learner with Contrastive Examples},
  author = {Wang, Chaoqi and Singla, Adish and Chen, Yuxin},
  booktitle = {Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  month = dec,
  month_name = {December},
  url = {https://arxiv.org/abs/2110.14888},
  venue = {NeurIPS},
  topic = {adaptive-learning}
}

Teaching via Best-Case Counterexamples in the Learning-with-Equivalence-Queries Paradigm

Akash Kumar, Yuxin Chen, Adish Singla

NeurIPS 2021

paper poster

bib

@inproceedings{kumar2021lweq,
  keywords = {active-learning, learning-theory},
  title = {Teaching via Best-Case Counterexamples in the Learning-with-Equivalence-Queries Paradigm},
  author = {Kumar, Akash and Chen, Yuxin and Singla, Adish},
  booktitle = {Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  month = dec,
  month_name = {December},
  url = {https://proceedings.neurips.cc/paper/2021/file/e22dd5dabde45eda5a1a67772c8e25dd-Paper.pdf},
  poster = {/files/papers/kumar21lweq-poster.pdf},
  venue = {NeurIPS},
  topic = {adaptive-learning}
}

Understanding the Effect of Bias in Deep Anomaly Detection

Ziyu Ye, Yuxin Chen, Haitao Zheng

IJCAI 2021

paper poster

bib

@inproceedings{ye2021anomdet,
  keywords = {other},
  title = {Understanding the Effect of Bias in Deep Anomaly Detection},
  author = {Ye, Ziyu and Chen, Yuxin and Zheng, Haitao},
  booktitle = {International Joint Conference on Artificial Intelligence (IJCAI)},
  note_venue = {Virtual},
  year = {2021},
  month = aug,
  month_name = {August},
  url = {https://arxiv.org/abs/2105.07346},
  poster = {/files/papers/ye21anomdet-poster.pdf},
  venue = {IJCAI},
  topic = {applications}
}

Learning to Make Decisions via Submodular Regularization

Ayya Alieva, Aiden Aceves, Jialin Song, Stephen Mayo, Yisong Yue, Yuxin Chen

ICLR 2021

paper poster

bib

@inproceedings{alieva2021submodular,
  keywords = {active-learning, bayesian-optimization},
  area = {active-learning},
  title = {Learning to Make Decisions via Submodular Regularization},
  author = {Alieva, Ayya and Aceves, Aiden and Song, Jialin and Mayo, Stephen and Yue, Yisong and Chen, Yuxin},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2021},
  month = may,
  month_name = {May},
  url = {https://openreview.net/forum?id=ac288vnG_7U},
  poster = {/files/papers/alieva21learning-poster.pdf},
  venue = {ICLR},
  topic = {decision-making}
}

The Teaching Dimension of Kernel Perceptron

Akash Kumar, Hanqi Zhang, Adish Singla, Yuxin Chen

AISTATS 2021

paper poster

bib

@inproceedings{kumar2021kernelperceptron,
  keywords = {active-learning, learning-theory},
  title = {The Teaching Dimension of Kernel Perceptron},
  author = {Kumar, Akash and Zhang, Hanqi and Singla, Adish and Chen, Yuxin},
  booktitle = {International Conference on Artificial Intelligence and Statistics (AISTATS)},
  year = {2021},
  month = apr,
  month_name = {April},
  url = {https://arxiv.org/abs/2010.14043},
  poster = {/files/papers/kumar20approxtd-poster.pdf},
  venue = {AISTATS},
  topic = {adaptive-learning}
}

Adaptive Teaching of Temporal Logic Formulas to Learners with Preferences

Zhe Xu, Yuxin Chen, Ufuk Topcu

AAAI 2021

paper

bib

@inproceedings{xu2021temporallogic,
  keywords = {active-learning, learning-theory},
  title = {Adaptive Teaching of Temporal Logic Formulas to Learners with Preferences},
  author = {Xu, Zhe and Chen, Yuxin and Topcu, Ufuk},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  month = feb,
  month_name = {February},
  url = {https://arxiv.org/pdf/2001.09956.pdf},
  venue = {AAAI},
  topic = {adaptive-learning}
}

2020

Design of Physical Experiments via Collision-Free Latent Space Optimization

Fengxue Zhang, Yair Altas, Louise Fan, Kaustubh Vinchure, Brian Nord, Yuxin Chen

NeurIPS ML4PS 2020

paper poster

bib

@inproceedings{zhang2020coflo,
  keywords = {bayesian-optimization, representation-learning, ai-for-science},
  title = {Design of Physical Experiments via Collision-Free Latent Space Optimization},
  author = {Zhang, Fengxue and Altas, Yair and Fan, Louise and Vinchure, Kaustubh and Nord, Brian and Chen, Yuxin},
  booktitle = {NeurIPS Workshop on Machine Learning and the Physical Sciences},
  year = {2020},
  month = dec,
  month_name = {December},
  url = {/files/papers/zhang20coflo.pdf},
  poster = {/files/papers/zhang20coflo-poster.pdf},
  venue = {NeurIPS ML4PS},
  topic = {ai4science}
}

Towards an Interpretable Data-driven Trigger System for High-throughput Physics Facilities

Chinmaya Mahesh, Kristin Dona, David W. Miller, Yuxin Chen

NeurIPS ML4PS 2020

paper poster

bib

@inproceedings{mahesh2020trigger,
  keywords = {ai-for-science},
  title = {Towards an Interpretable Data-driven Trigger System for High-throughput Physics Facilities},
  author = {Mahesh, Chinmaya and Dona, Kristin and Miller, David W. and Chen, Yuxin},
  booktitle = {NeurIPS Workshop on Machine Learning and the Physical Sciences},
  year = {2020},
  month = dec,
  month_name = {December},
  url = {/files/papers/mahesh21trigger.pdf},
  poster = {/files/papers/mahesh21trigger-poster.pdf},
  venue = {NeurIPS ML4PS},
  topic = {ai4science}
}

Understanding the Power and Limitations of Teaching with Imperfect Knowledge

Rati Devidze, Farnam Mansouri, Luis Haug, Yuxin Chen, Adish Singla

IJCAI 2020

paper

bib

@inproceedings{devidze2020imperfect,
  keywords = {active-learning, learning-theory},
  title = {Understanding the Power and Limitations of Teaching with Imperfect Knowledge},
  author = {Devidze, Rati and Mansouri, Farnam and Haug, Luis and Chen, Yuxin and Singla, Adish},
  booktitle = {International Joint Conference on Artificial Intelligence (IJCAI)},
  note_venue = {Virtual},
  year = {2020},
  month = jul,
  url = {https://arxiv.org/abs/2003.09712.pdf},
  venue = {IJCAI},
  topic = {adaptive-learning}
}

An Online Learning Framework for Energy-Efficient Navigation of Electric Vehicles

Niklas Åkerblom, Yuxin Chen, Morteza Haghir Chehreghani

IJCAI 2020

paper extended version

bib

@inproceedings{akerblom2020ev,
  keywords = {reinforcement-learning},
  title = {An Online Learning Framework for Energy-Efficient Navigation of Electric Vehicles},
  author = {Åkerblom, Niklas and Chen, Yuxin and Chehreghani, Morteza Haghir},
  booktitle = {International Joint Conference on Artificial Intelligence (IJCAI)},
  note_venue = {Virtual},
  year = {2020},
  month = jul,
  url = {https://arxiv.org/abs/2003.01416.pdf},
  extra_links = {extended version},
  venue = {IJCAI},
  topic = {decision-making}
}

Mirrored Plasmonic Filter Design via Active Learning of Multi-Fidelity Physical Models

Jialin Song, Yury S. Tokpanov, Yuxin Chen, Dagny Fleischman, Katherine T. Fountaine, Yisong Yue, Harry A. Atwater

CLEO 2020

paper

bib

@inproceedings{song2020cleo,
  keywords = {bayesian-optimization, ai-for-science},
  title = {Mirrored Plasmonic Filter Design via Active Learning of Multi-Fidelity Physical Models},
  author = {Song, Jialin and Tokpanov, Yury S. and Chen, Yuxin and Fleischman, Dagny and Fountaine, Katherine T. and Yue, Yisong and Atwater, Harry A.},
  booktitle = {IEEE Conference on Lasers and Electro-Optics (CLEO)},
  year = {2020},
  month = may,
  month_name = {May},
  link = {https://ieeexplore.ieee.org/abstract/document/9192854},
  venue = {CLEO},
  topic = {ai4science}
}

2019

Preference-Based Batch and Sequential Teaching: Towards a Unified View of Models

Farnam Mansouri, Yuxin Chen, Ara Vartanian, Xiaojin Zhu, Adish Singla

NeurIPS 2019

paper poster

bib

@inproceedings{mansouri2019tdsigma,
  keywords = {active-learning, learning-theory},
  title = {Preference-Based Batch and Sequential Teaching: Towards a Unified View of Models},
  author = {Mansouri, Farnam and Chen, Yuxin and Vartanian, Ara and Zhu, Xiaojin and Singla, Adish},
  booktitle = {Neural Information Processing Systems (NeurIPS)},
  note_venue = {Vancouver, Canada},
  year = {2019},
  month = dec,
  month_name = {December},
  url = {https://arxiv.org/pdf/1910.10944.pdf},
  poster = {/files/papers/mansouri19tdsigma-poster.pdf},
  venue = {NeurIPS},
  topic = {adaptive-learning}
}

Landmark Ordinal Embedding

Nikhil Ghosh, Yuxin Chen, Yisong Yue

NeurIPS 2019

paper poster

bib

@inproceedings{ghosh2019loe,
  keywords = {active-learning, representation-learning, learning-theory},
  title = {Landmark Ordinal Embedding},
  author = {Ghosh, Nikhil and Chen, Yuxin and Yue, Yisong},
  booktitle = {Neural Information Processing Systems (NeurIPS)},
  note_venue = {Vancouver, Canada},
  year = {2019},
  month = dec,
  month_name = {December},
  url = {https://arxiv.org/pdf/1910.12379.pdf},
  poster = {/files/papers/ghosh19loe-poster.pdf},
  venue = {NeurIPS},
  topic = {adaptive-learning}
}

Teaching Multiple Concepts to Forgetful Learners

Anette Hunziker, Yuxin Chen, Oisin Mac Aodha, Manuel Gomez Rodriguez, Andreas Krause, Pietro Perona, Yisong Yue, Adish Singla

NeurIPS 2019

paper poster

bib

@inproceedings{hunziker2019forgetful,
  keywords = {active-learning, learning-theory},
  title = {Teaching Multiple Concepts to Forgetful Learners},
  author = {Hunziker, Anette and Chen, Yuxin and Aodha, Oisin Mac and Rodriguez, Manuel Gomez and Krause, Andreas and Perona, Pietro and Yue, Yisong and Singla, Adish},
  booktitle = {Neural Information Processing Systems (NeurIPS)},
  note_venue = {Vancouver, Canada},
  year = {2019},
  month = dec,
  month_name = {December},
  url = {https://arxiv.org/pdf/1805.08322.pdf},
  poster = {/files/papers/hunziker19forgetful-poster.pdf},
  venue = {NeurIPS},
  topic = {adaptive-learning}
}

An Encoder-Decoder Based Approach for Anomaly Detection with Application in Additive Manufacturing

Baihong Jin, Yingshui Tan, Alexander Nettekoven, Yuxin Chen, Ufuk Topcu, Yisong Yue, Alberto Sangiovanni Vincentelli

ICMLA 2019

paper

bib

@inproceedings{jin2019encdec,
  keywords = {other},
  title = {An Encoder-Decoder Based Approach for Anomaly Detection with Application in Additive Manufacturing},
  author = {Jin, Baihong and Tan, Yingshui and Nettekoven, Alexander and Chen, Yuxin and Topcu, Ufuk and Yue, Yisong and Vincentelli, Alberto Sangiovanni},
  booktitle = {IEEE International Conference on Machine Learning and Applications (ICMLA)},
  note_venue = {Boca Raton, USA},
  year = {2019},
  month = dec,
  month_name = {December},
  url = {https://arxiv.org/pdf/1907.11778.pdf},
  venue = {ICMLA},
  topic = {applications}
}

Barrier Certificates for Assured Machine Teaching

Mohamadreza Ahmadi, Bo Wu, Yuxin Chen, Yisong Yue, Ufuk Topcu

ACC 2019

paper

bib

@inproceedings{ahmadi2019barrier,
  keywords = {active-learning, learning-theory},
  title = {Barrier Certificates for Assured Machine Teaching},
  author = {Ahmadi, Mohamadreza and Wu, Bo and Chen, Yuxin and Yue, Yisong and Topcu, Ufuk},
  booktitle = {American Control Conference (ACC)},
  note_venue = {Philadelphia},
  year = {2019},
  month = jul,
  month_name = {July},
  url = {https://arxiv.org/abs/1810.00093.pdf},
  venue = {ACC},
  topic = {adaptive-learning}
}

A One-Class Support Vector Machine Calibration Method for Time Series Change Point Detection

Baihong Jin, Yuxin Chen, Dan Li, Kameshwar Poolla, Alberto L. Sangiovanni-Vincentelli

ICPHM 2019

paper

bib

@inproceedings{jin2019oneclass,
  keywords = {other},
  title = {A One-Class Support Vector Machine Calibration Method for Time Series Change Point Detection},
  author = {Jin, Baihong and Chen, Yuxin and Li, Dan and Poolla, Kameshwar and Sangiovanni-Vincentelli, Alberto L.},
  booktitle = {IEEE International Conference on Prognostics and Health Management (ICPHM)},
  note_venue = {San Francisco, USA},
  year = {2019},
  month = jun,
  month_name = {June},
  url = {https://arxiv.org/pdf/1902.06361.pdf},
  venue = {ICPHM},
  topic = {applications}
}

Batched Stochastic Bayesian Optimization via Combinatorial Constraints Design

Kevin Yang, Yuxin Chen, Alycia Lee, Yisong Yue

AISTATS 2019

paper poster

bib

@inproceedings{yang2019bsbo,
  keywords = {bayesian-optimization, ai-for-science},
  title = {Batched Stochastic Bayesian Optimization via Combinatorial Constraints Design},
  author = {Yang, Kevin and Chen, Yuxin and Lee, Alycia and Yue, Yisong},
  booktitle = {International Conference on Artificial Intelligence and Statistics (AISTATS)},
  note_venue = {Naha, Okinawa, Japan},
  year = {2019},
  month = apr,
  month_name = {April},
  url = {https://arxiv.org/pdf/1904.08102.pdf},
  poster = {/files/papers/yang19bsbo-poster.pdf},
  prelim = {NeurIPS Workshop on Machine Learning for Molecules and Materials, December 2018},
  venue = {AISTATS},
  topic = {decision-making}
}

Preliminary version: NeurIPS Workshop on Machine Learning for Molecules and Materials, December 2018.

A General Framework for Multi-fidelity Bayesian Optimization with Gaussian Processes

Jialin Song, Yuxin Chen, Yisong Yue

AISTATS 2019

paper poster

bib

@inproceedings{song2019gpopt,
  keywords = {bayesian-optimization, learning-theory},
  area = {bayesian-optimization},
  title = {A General Framework for Multi-fidelity Bayesian Optimization with Gaussian Processes},
  author = {Song, Jialin and Chen, Yuxin and Yue, Yisong},
  booktitle = {International Conference on Artificial Intelligence and Statistics (AISTATS)},
  note_venue = {Naha, Okinawa, Japan},
  year = {2019},
  month = apr,
  month_name = {April},
  url = {https://arxiv.org/abs/1811.00755.pdf},
  poster = {/files/papers/song19gpopt-poster.pdf},
  venue = {AISTATS},
  topic = {decision-making}
}

2018

Understanding the Role of Adaptivity in Machine Teaching: The Case of Version Space Learners

Yuxin Chen, Adish Singla, Oisin Mac Aodha, Pietro Perona, Yisong Yue

NeurIPS 2018

paper poster

bib

@inproceedings{chen2018adaptive,
  keywords = {active-learning, learning-theory},
  title = {Understanding the Role of Adaptivity in Machine Teaching: The Case of Version Space Learners},
  author = {Chen, Yuxin and Singla, Adish and Aodha, Oisin Mac and Perona, Pietro and Yue, Yisong},
  booktitle = {Neural Information Processing Systems (NeurIPS)},
  note_venue = {Montreal, Canada},
  year = {2018},
  month = dec,
  month_name = {December},
  url = {https://arxiv.org/pdf/1802.05190.pdf},
  poster = {/files/papers/chen18adaptive-poster.pdf},
  venue = {NeurIPS},
  topic = {adaptive-learning}
}

Optimizing Photonic Nanostructures via Multi-fidelity Gaussian Processes

Jialin Song, Yury S. Tokpanov, Yuxin Chen, Dagny Fleischman, Kate T. Fountaine, Harry A. Atwater, Yisong Yue

NeurIPS ML4Molecules 2018

bib

@inproceedings{song2018nanophotonics,
  keywords = {bayesian-optimization, ai-for-science},
  title = {Optimizing Photonic Nanostructures via Multi-fidelity Gaussian Processes},
  author = {Song, Jialin and Tokpanov, Yury S. and Chen, Yuxin and Fleischman, Dagny and Fountaine, Kate T. and Atwater, Harry A. and Yue, Yisong},
  booktitle = {NeurIPS Workshop on Machine Learning for Molecules and Materials},
  note_venue = {Montreal, Canada},
  year = {2018},
  month = dec,
  month_name = {December},
  venue = {NeurIPS ML4Molecules},
  topic = {ai4science}
}

Teaching Categories to Human Learners with Visual Explanations

Oisin Mac Aodha, Shihan Su, Yuxin Chen, Pietro Perona, Yisong Yue

CVPR 2018 Spotlight presentation

paper

bib

@inproceedings{macaodha2018teaching,
  keywords = {active-learning},
  title = {Teaching Categories to Human Learners with Visual Explanations},
  author = {Aodha, Oisin Mac and Su, Shihan and Chen, Yuxin and Perona, Pietro and Yue, Yisong},
  booktitle = {Conference on Computer Vision and Pattern Recognition (CVPR)},
  note_venue = {Salt Lake City, UT},
  year = {2018},
  month = apr,
  month_name = {April},
  award = {Spotlight presentation},
  url = {https://arxiv.org/abs/1802.06924},
  venue = {CVPR},
  topic = {adaptive-learning}
}

Near-Optimal Machine Teaching via Explanatory Teaching Sets

Yuxin Chen, Oisin Mac Aodha, Shihan Su, Pietro Perona, Yisong Yue

AISTATS 2018

paper poster long version

bib

@inproceedings{chen2018notes,
  keywords = {active-learning, learning-theory},
  title = {Near-Optimal Machine Teaching via Explanatory Teaching Sets},
  author = {Chen, Yuxin and Aodha, Oisin Mac and Su, Shihan and Perona, Pietro and Yue, Yisong},
  booktitle = {International Conference on Artificial Intelligence and Statistics (AISTATS)},
  note_venue = {Playa Blanca, Lanzarote, Canary Islands},
  year = {2018},
  month = apr,
  month_name = {April},
  url = {/files/papers/chen18notes.pdf},
  poster = {/files/papers/chen18notes-poster.pdf},
  extra_links = {long version},
  venue = {AISTATS},
  topic = {adaptive-learning}
}

2017 and earlier

Interpretable Machine Teaching via Feature Feedback

Shihan Su, Yuxin Chen, Oisin Mac Aodha, Pietro Perona, Yisong Yue

NeurIPS TMRH 2017

paper poster

bib

@inproceedings{su2017featurefb,
  keywords = {active-learning},
  title = {Interpretable Machine Teaching via Feature Feedback},
  author = {Su, Shihan and Chen, Yuxin and Aodha, Oisin Mac and Perona, Pietro and Yue, Yisong},
  booktitle = {NeurIPS Workshop on Teaching Machines, Robots, and Humans},
  year = {2017},
  month = dec,
  month_name = {December},
  url = {http://teaching-machines.cc/nips2017/papers/nips17-teaching_paper-5.pdf},
  poster = {/files/papers/su17featurefb-poster.pdf},
  venue = {NeurIPS TMRH},
  topic = {adaptive-learning}
}

Learning Shape Analysis

Marc Brockschmidt, Yuxin Chen, Pushmeet Kohli, Siddharth Krishna, Daniel Tarlow

SAS 2017

paper doi

bib

@inproceedings{brockschmidt2017shape,
  keywords = {other},
  title = {Learning Shape Analysis},
  author = {Brockschmidt, Marc and Chen, Yuxin and Kohli, Pushmeet and Krishna, Siddharth and Tarlow, Daniel},
  booktitle = {24th Static Analysis Symposium (SAS)},
  note_venue = {New York City, NY},
  year = {2017},
  month = aug,
  month_name = {August},
  url = {https://link.springer.com/content/pdf/10.1007%2F978-3-319-66706-5_4.pdf},
  doi = {10.1007/978-3-319-66706-5_4},
  venue = {SAS},
  topic = {applications}
}

Efficient Online Learning for Optimizing Value of Information: Theory and Application to Interactive Troubleshooting

Yuxin Chen, Jean-Michel Renders, Morteza Haghir Chehreghani, Andreas Krause

UAI 2017

paper poster

bib

@inproceedings{chen2017onlinevoi,
  keywords = {active-learning},
  title = {Efficient Online Learning for Optimizing Value of Information: Theory and Application to Interactive Troubleshooting},
  author = {Chen, Yuxin and Renders, Jean-Michel and Chehreghani, Morteza Haghir and Krause, Andreas},
  booktitle = {Conference on Uncertainty in Artificial Intelligence (UAI)},
  note_venue = {Sydney, Australia},
  year = {2017},
  month = aug,
  month_name = {August},
  url = {/files/papers/chen17onlinevoi.pdf},
  poster = {/files/papers/chen17onlinevoi-poster.pdf},
  venue = {UAI},
  topic = {adaptive-learning}
}

Near-optimal Bayesian Active Learning with Correlated and Noisy Tests

Yuxin Chen, Hamed Hassani, Andreas Krause

AISTATS 2017 Oral presentation

paper poster long version journal version

bib

@inproceedings{chen2017eced,
  keywords = {active-learning, learning-theory},
  area = {active-learning},
  title = {Near-optimal Bayesian Active Learning with Correlated and Noisy Tests},
  author = {Chen, Yuxin and Hassani, Hamed and Krause, Andreas},
  booktitle = {International Conference on Artificial Intelligence and Statistics (AISTATS)},
  note_venue = {Fort Lauderdale, FL},
  year = {2017},
  month = apr,
  month_name = {April},
  award = {Oral presentation},
  url = {/files/papers/chen17eced.pdf},
  poster = {/files/papers/chen17eced-poster.pdf},
  extra_links = {long version journal version},
  prelim = {Extended version published in the Electronic Journal of Statistics (EJS), Volume 11, 2017},
  venue = {AISTATS},
  topic = {adaptive-learning}
}

Preliminary version: Extended version published in the Electronic Journal of Statistics (EJS), Volume 11, 2017.

Learning to Verify the Heap

Marc Brockschmidt, Yuxin Chen, Byron Cook, Pushmeet Kohli, Siddharth Krishna, Daniel Tarlow, He Zhu

MSR-TR 2016

paper poster

bib

@techreport{brockschmidt2016heap,
  keywords = {other},
  title = {Learning to Verify the Heap},
  author = {Brockschmidt, Marc and Chen, Yuxin and Cook, Byron and Kohli, Pushmeet and Krishna, Siddharth and Tarlow, Daniel and Zhu, He},
  institution = {Microsoft Research},
  number = {MSR-TR-2016-17},
  year = {2016},
  month = jun,
  month_name = {June},
  url = {https://www.microsoft.com/en-us/research/wp-content/uploads/2016/06/veriml-1.pdf},
  poster = {/files/papers/brockschmidt15heap-poster.pdf},
  venue = {MSR-TR},
  topic = {applications}
}

Sequential Information Maximization: When is Greedy Near-optimal?

Yuxin Chen, Hamed Hassani, Amin Karbasi, Andreas Krause

COLT 2015

paper poster talk

bib

@inproceedings{chen2015mis,
  keywords = {active-learning, learning-theory},
  title = {Sequential Information Maximization: When is Greedy Near-optimal?},
  author = {Chen, Yuxin and Hassani, Hamed and Karbasi, Amin and Krause, Andreas},
  booktitle = {28th Annual Conference on Learning Theory (COLT)},
  note_venue = {Paris, France},
  year = {2015},
  month = jul,
  month_name = {July},
  url = {http://las.ethz.ch/files/chen15mis.pdf},
  poster = {/files/papers/chen15mis-poster.pdf},
  talk = {http://videolectures.net/colt2015_chen_information_maximization/},
  venue = {COLT},
  topic = {adaptive-learning}
}

Learning to Decipher the Heap for Program Verification

Marc Brockschmidt, Yuxin Chen, Byron Cook, Pushmeet Kohli, Daniel Tarlow

ICML CML 2015 Winner of the Best Paper Award

paper

bib

@inproceedings{brockschmidt2015decipher,
  keywords = {other},
  title = {Learning to Decipher the Heap for Program Verification},
  author = {Brockschmidt, Marc and Chen, Yuxin and Cook, Byron and Kohli, Pushmeet and Tarlow, Daniel},
  booktitle = {ICML Workshop on Constructive Machine Learning (CML)},
  note_venue = {Lille, France},
  year = {2015},
  month = jul,
  month_name = {July},
  award = {Winner of the Best Paper Award},
  url = {/files/papers/brockschmidt15heap.pdf},
  venue = {ICML CML},
  topic = {applications}
}

Submodular Surrogates for Value of Information

Yuxin Chen, Shervin Javdani, Amin Karbasi, Drew Bagnell, Siddhartha Srinivasa, Andreas Krause

AAAI 2015

paper poster long version

bib

@inproceedings{chen2015submodular,
  keywords = {active-learning, learning-theory},
  title = {Submodular Surrogates for Value of Information},
  author = {Chen, Yuxin and Javdani, Shervin and Karbasi, Amin and Bagnell, Drew and Srinivasa, Siddhartha and Krause, Andreas},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  note_venue = {Austin, TX},
  year = {2015},
  month = jan,
  month_name = {January},
  url = {http://las.ethz.ch/files/chen15submsrgtvoi.pdf},
  poster = {/files/papers/chen14submsrgtvoi-poster.pdf},
  extra_links = {long version},
  prelim = {NeurIPS Workshop on Discrete Optimization in Machine Learning (DISCML), December 2014},
  venue = {AAAI},
  topic = {adaptive-learning}
}

Preliminary version: NeurIPS Workshop on Discrete Optimization in Machine Learning (DISCML), December 2014.

Decision Region Determination for Touch Based Localization

Shervin Javdani, Yuxin Chen, Amin Karbasi, Drew Bagnell, Siddhartha Srinivasa, Andreas Krause

RSS Workshop 2014

paper talk

bib

@inproceedings{javdani2014touch,
  keywords = {active-learning},
  title = {Decision Region Determination for Touch Based Localization},
  author = {Javdani, Shervin and Chen, Yuxin and Karbasi, Amin and Bagnell, Drew and Srinivasa, Siddhartha and Krause, Andreas},
  booktitle = {RSS Workshop on Information-based Grasp and Manipulation Planning},
  year = {2014},
  month = jul,
  month_name = {July},
  url = {http://www.cs.cmu.edu/~sjavdani/papers/rss_2014_workshop_abstract.pdf},
  talk = {https://www.youtube.com/watch?v=20KuxPd01PE},
  venue = {RSS Workshop},
  topic = {adaptive-learning}
}

Active Detection via Adaptive Submodularity

Yuxin Chen, Hiroaki Shioi, Cesar Antonio Fuentes Montesinos, Lian Pin Koh, Serge Wich, Andreas Krause

ICML 2014

paper poster talk long version

bib

@inproceedings{chen2014active,
  keywords = {active-learning},
  title = {Active Detection via Adaptive Submodularity},
  author = {Chen, Yuxin and Shioi, Hiroaki and Montesinos, Cesar Antonio Fuentes and Koh, Lian Pin and Wich, Serge and Krause, Andreas},
  booktitle = {International Conference on Machine Learning (ICML)},
  note_venue = {Beijing, China},
  year = {2014},
  month = jun,
  month_name = {June},
  url = {http://las.ethz.ch/files/chen14active.pdf},
  poster = {http://www.its.caltech.edu/~chenyux/files/papers/chen13objectdet-poster.pdf},
  talk = {http://techtalks.tv/talks/active-detection-via-adaptive-submodularity/61056/},
  extra_links = {long version},
  prelim = {NeurIPS Workshop on Machine Learning for Sustainability (MLSUST), December 2013},
  venue = {ICML},
  topic = {adaptive-learning}
}

Preliminary version: NeurIPS Workshop on Machine Learning for Sustainability (MLSUST), December 2013.

Near-Optimal Bayesian Active Learning for Decision Making

Shervin Javdani, Yuxin Chen, Amin Karbasi, Andreas Krause, Drew Bagnell, Siddhartha Srinivasa

AISTATS 2014

paper long version

bib

@inproceedings{javdani2014near,
  keywords = {active-learning},
  title = {Near-Optimal Bayesian Active Learning for Decision Making},
  author = {Javdani, Shervin and Chen, Yuxin and Karbasi, Amin and Krause, Andreas and Bagnell, Drew and Srinivasa, Siddhartha},
  booktitle = {International Conference on Artificial Intelligence and Statistics (AISTATS)},
  note_venue = {Reykjavik, Iceland},
  year = {2014},
  month = apr,
  month_name = {April},
  url = {http://las.ethz.ch/files/javdani14near.pdf},
  extra_links = {long version},
  venue = {AISTATS},
  topic = {adaptive-learning}
}

iLike: Bridging the Semantic Gap in Vertical Image Search by Integrating Text and Visual Features

Yuxin Chen, Hariprasad Sampathkumar, Bo Luo, Xue-wen Chen

TKDE 2013

paper doi

bib

@article{chen2013ilike,
  keywords = {other},
  title = {iLike: Bridging the Semantic Gap in Vertical Image Search by Integrating Text and Visual Features},
  author = {Chen, Yuxin and Sampathkumar, Hariprasad and Luo, Bo and Chen, Xue-wen},
  journal = {IEEE Transactions on Knowledge and Data Engineering (TKDE)},
  year = {2013},
  month = oct,
  month_name = {October},
  link = {http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6378368},
  doi = {10.1109/TKDE.2012.192},
  venue = {TKDE},
  topic = {applications}
}

Near-optimal Batch Mode Active Learning and Adaptive Submodular Optimization

Yuxin Chen, Andreas Krause

ICML 2013

paper poster talk long version spotlight

bib

@inproceedings{chen2013near,
  keywords = {active-learning, learning-theory},
  title = {Near-optimal Batch Mode Active Learning and Adaptive Submodular Optimization},
  author = {Chen, Yuxin and Krause, Andreas},
  booktitle = {International Conference on Machine Learning (ICML)},
  note_venue = {Atlanta, GA},
  year = {2013},
  month = jun,
  month_name = {June},
  url = {http://las.ethz.ch/files/chen13near.pdf},
  poster = {/files/papers/chen13near-poster.pdf},
  talk = {http://techtalks.tv/talks/near-optimal-batch-mode-active-learning-and-adaptive-submodular-optimization/58410/},
  extra_links = {long version spotlight},
  prelim = {NeurIPS Workshop on Discrete Optimization in Machine Learning (DISCML), December 2012},
  venue = {ICML},
  topic = {adaptive-learning}
}

Preliminary version: NeurIPS Workshop on Discrete Optimization in Machine Learning (DISCML), December 2012.

IPKB: A Digital Library for Invertebrate Paleontology

Yuanliang Meng, Junyan Li, Patrick Denton, Yuxin Chen, Bo Luo, Paul Selden, Xue-wen Chen

JCDL 2012

paper doi

bib

@inproceedings{meng2012ipkb,
  keywords = {other},
  title = {IPKB: A Digital Library for Invertebrate Paleontology},
  author = {Meng, Yuanliang and Li, Junyan and Denton, Patrick and Chen, Yuxin and Luo, Bo and Selden, Paul and Chen, Xue-wen},
  booktitle = {12th ACM/IEEE-CS Joint Conference on Digital Libraries (JCDL)},
  note_venue = {Washington DC},
  year = {2012},
  month = jun,
  month_name = {June},
  url = {/files/papers/meng2012ipkb.pdf},
  doi = {10.1145/2232817.2232837},
  venue = {JCDL},
  topic = {applications}
}

S2A: Secure Smart Household Appliances

Yuxin Chen, Bo Luo

CODASPY 2012

paper doi

bib

@inproceedings{chen2012s2a,
  keywords = {other},
  title = {S2A: Secure Smart Household Appliances},
  author = {Chen, Yuxin and Luo, Bo},
  booktitle = {2nd ACM Conference on Data and Application Security and Privacy (CODASPY)},
  note_venue = {San Antonio, TX},
  year = {2012},
  month = feb,
  month_name = {February},
  link = {http://dl.acm.org/ft_gateway.cfm?id=2133628&ftid=1128030&dwn=1&CFID=169703878&CFTOKEN=79594521},
  doi = {10.1145/2133601.2133628},
  venue = {CODASPY},
  topic = {applications}
}

Cephalometric Landmark Tracing Using Deformable Templates

Yuxin Chen, Brian Potetz, Bo Luo, Xue-wen Chen

HISB 2011

paper slides doi

bib

@inproceedings{chen2011cepha,
  keywords = {other},
  title = {Cephalometric Landmark Tracing Using Deformable Templates},
  author = {Chen, Yuxin and Potetz, Brian and Luo, Bo and Chen, Xue-wen},
  booktitle = {1st IEEE Conference on Healthcare Informatics, Imaging, and Systems Biology (HISB)},
  note_venue = {San Jose, CA},
  year = {2011},
  month = jul,
  month_name = {July},
  link = {http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6061381},
  slides = {/files/papers/chen11cephalometry-slides.pdf},
  doi = {10.1109/HISB.2011.14},
  venue = {HISB},
  topic = {applications}
}

Privacy-Preserving Group Linkage

Fengjun Li, Yuxin Chen, Bo Luo, Dongwon Lee, Peng Liu

SSDBM 2011

paper slides doi

bib

@inproceedings{li2011privacy,
  keywords = {other},
  title = {Privacy-Preserving Group Linkage},
  author = {Li, Fengjun and Chen, Yuxin and Luo, Bo and Lee, Dongwon and Liu, Peng},
  booktitle = {23rd Scientific and Statistical Database Management Conference (SSDBM)},
  note_venue = {Portland, OR},
  year = {2011},
  month = jul,
  month_name = {July},
  url = {http://pike.psu.edu/publications/ssdbm11.pdf},
  slides = {/files/papers/li11ppgl-luo-slides.pdf},
  doi = {10.1007/978-3-642-22351-8_27},
  venue = {SSDBM},
  topic = {applications}
}

iLike: Integrating Visual and Textual Features for Vertical Search

Yuxin Chen, Nenghai Yu, Bo Luo, Xue-wen Chen

ACMMM 2010

paper slides doi

bib

@inproceedings{chen2010ilike,
  keywords = {other},
  title = {iLike: Integrating Visual and Textual Features for Vertical Search},
  author = {Chen, Yuxin and Yu, Nenghai and Luo, Bo and Chen, Xue-wen},
  booktitle = {ACM Multimedia Conference (ACMMM)},
  note_venue = {Firenze, Italy},
  year = {2010},
  month = oct,
  month_name = {October},
  url = {http://ittc.ku.edu/~bluo/download/mm10.PDF},
  slides = {/files/papers/bluo10ilike-slides.pdf},
  doi = {10.1145/1873951.1873984},
  venue = {ACMMM},
  topic = {applications}
}

Preprints

Shared Actors Need Not Share Critics: Effects of Value Mismatch in Parallel Reinforcement Learning

Zhenya Liu, Yang Meng, Zhuokai Zhao, Xuefeng Liu, Yuxin Chen

Preprint, arXiv:2608.26481, 2026

paper project

bib

@misc{liu2026sharedactors,
  keywords = {reinforcement-learning},
  title = {Shared Actors Need Not Share Critics: Effects of Value Mismatch in Parallel Reinforcement Learning},
  author = {Liu, Zhenya and Meng, Yang and Zhao, Zhuokai and Liu, Xuefeng and Chen, Yuxin},
  howpublished = {Preprint, arXiv:2608.26481},
  year = {2026},
  month = aug,
  url = {https://arxiv.org/abs/2608.26481},
  website = {https://liu-zhenya.github.io/shared-actors-need-not-share-critics/},
  venue = {arXiv},
  topic = {decision-making}
}

Rethinking Transfer in Continual Learning: A Replay-Based Realisation

Yang Meng, Zhenya Liu, Zhuokai Zhao, Yuxin Chen

Preprint, arXiv:2607.15587, 2026

paper

bib

@misc{meng2026transfer,
  keywords = {reinforcement-learning},
  title = {Rethinking Transfer in Continual Learning: A Replay-Based Realisation},
  author = {Meng, Yang and Liu, Zhenya and Zhao, Zhuokai and Chen, Yuxin},
  howpublished = {Preprint, arXiv:2607.15587},
  year = {2026},
  month = jul,
  url = {https://arxiv.org/abs/2607.15587},
  venue = {arXiv},
  topic = {decision-making}
}

Constrained Bayesian Optimization with Adaptive Active Learning of Unknown Constraints

Fengxue Zhang, Zejie Zhu, Yuxin Chen

Preprint, arXiv:2310.08751, 2023

paper

bib

@misc{zhang2023constraints,
  keywords = {bayesian-optimization},
  title = {Constrained Bayesian Optimization with Adaptive Active Learning of Unknown Constraints},
  author = {Zhang, Fengxue and Zhu, Zejie and Chen, Yuxin},
  howpublished = {Preprint, arXiv:2310.08751},
  year = {2023},
  month = oct,
  url = {http://arxiv.org/abs/2310.08751},
  venue = {arXiv},
  topic = {decision-making}
}

Learning Representation for Bayesian Optimization with Collision-free Regularization

Fengxue Zhang, Brian Nord, Yuxin Chen

Preprint, arXiv:2203.08656, 2022

paper

bib

@misc{zhang2022colreg,
  keywords = {bayesian-optimization, representation-learning},
  title = {Learning Representation for Bayesian Optimization with Collision-free Regularization},
  author = {Zhang, Fengxue and Nord, Brian and Chen, Yuxin},
  howpublished = {Preprint, arXiv:2203.08656},
  year = {2022},
  month = mar,
  url = {https://arxiv.org/abs/2203.08656},
  venue = {arXiv},
  topic = {decision-making}
}

Rethinking Explainability as a Dialogue: A Practitioner’s Perspective

Himabindu Lakkaraju, Dylan Slack, Yuxin Chen, Chenhao Tan, Sameer Singh

Preprint, arXiv:2202.01875, 2022

paper

bib

@misc{lakkaraju2022dialogue,
  keywords = {other},
  title = {Rethinking Explainability as a Dialogue: A Practitioner's Perspective},
  author = {Lakkaraju, Himabindu and Slack, Dylan and Chen, Yuxin and Tan, Chenhao and Singh, Sameer},
  howpublished = {Preprint, arXiv:2202.01875},
  year = {2022},
  month = feb,
  url = {https://arxiv.org/abs/2202.01875},
  venue = {arXiv},
  topic = {applications}
}

Preference-Based Batch and Sequential Teaching

Farnam Mansouri, Yuxin Chen, Ara Vartanian, Xiaojin Zhu, Adish Singla

Preprint, arXiv:2010.10012 (extended version of the NeurIPS’19 paper), 2020

paper

bib

@misc{mansouri2020pbst,
  keywords = {active-learning, learning-theory},
  title = {Preference-Based Batch and Sequential Teaching},
  author = {Mansouri, Farnam and Chen, Yuxin and Vartanian, Ara and Zhu, Xiaojin and Singla, Adish},
  howpublished = {Preprint, arXiv:2010.10012 (extended version of the NeurIPS'19 paper)},
  year = {2020},
  month = oct,
  url = {https://arxiv.org/abs/2010.10012},
  venue = {arXiv},
  topic = {adaptive-learning}
}

Exploiting Uncertainties from Ensemble Learners to Improve Decision-Making in Healthcare AI

Yingshui Tan, Baihong Jin, Xiangyu Yue, Yuxin Chen, Alberto Sangiovanni Vincentelli

Preprint, arXiv:2007.06063, 2020

paper

bib

@misc{tan2020uncertainties,
  keywords = {other},
  title = {Exploiting Uncertainties from Ensemble Learners to Improve Decision-Making in Healthcare AI},
  author = {Tan, Yingshui and Jin, Baihong and Yue, Xiangyu and Chen, Yuxin and Vincentelli, Alberto Sangiovanni},
  howpublished = {Preprint, arXiv:2007.06063},
  year = {2020},
  month = jul,
  url = {https://arxiv.org/abs/2007.06063},
  venue = {arXiv},
  topic = {applications}
}

Are Ensemble Classifiers Powerful Enough for the Detection and Diagnosis of Intermediate-Severity Faults?

Baihong Jin, Yingshui Tan, Yuxin Chen, Kameshwar Poolla, Alberto Sangiovanni Vincentelli

Preprint, arXiv:2007.03167, 2020

paper

bib

@misc{jin2020ensemble,
  keywords = {other},
  title = {Are Ensemble Classifiers Powerful Enough for the Detection and Diagnosis of Intermediate-Severity Faults?},
  author = {Jin, Baihong and Tan, Yingshui and Chen, Yuxin and Poolla, Kameshwar and Vincentelli, Alberto Sangiovanni},
  howpublished = {Preprint, arXiv:2007.03167},
  year = {2020},
  month = jul,
  url = {https://arxiv.org/abs/2007.03167},
  venue = {arXiv},
  topic = {applications}
}

Average-case Complexity of Teaching Convex Polytopes via Halfspace Queries

Akash Kumar, Adish Singla, Yisong Yue, Yuxin Chen

Preprint, arXiv:2006.14677, 2020

paper

bib

@misc{kumar2020polytopes,
  keywords = {active-learning, learning-theory},
  title = {Average-case Complexity of Teaching Convex Polytopes via Halfspace Queries},
  author = {Kumar, Akash and Singla, Adish and Yue, Yisong and Chen, Yuxin},
  howpublished = {Preprint, arXiv:2006.14677},
  year = {2020},
  month = jun,
  url = {https://arxiv.org/abs/2006.14677},
  venue = {arXiv},
  topic = {adaptive-learning}
}

Theses

Near-optimal Adaptive Information Acquisition: Theory and Applications

Yuxin Chen

PhD thesis, ETH Zurich, 2017

paper doi

bib

@phdthesis{chen2017phdthesis,
  keywords = {active-learning},
  title = {Near-optimal Adaptive Information Acquisition: Theory and Applications},
  author = {Chen, Yuxin},
  school = {ETH Zurich},
  year = {2017},
  month = feb,
  month_name = {February},
  url = {/files/theses/chen17-phdthesis.pdf},
  doi = {10.3929/ethz-b-000000139},
  venue = {ETH Zurich},
  topic = {adaptive-learning}
}

Understanding User Intentions in Vertical Image Search

Yuxin Chen

Master's thesis, The University of Kansas, 2011

paper url

bib

@mastersthesis{chen2011msthesis,
  keywords = {other},
  title = {Understanding User Intentions in Vertical Image Search},
  author = {Chen, Yuxin},
  school = {The University of Kansas},
  year = {2011},
  month = aug,
  month_name = {August},
  url = {/files/theses/chen11vertical-msthesis.pdf},
  link = {https://kuscholarworks.ku.edu/handle/1808/10419},
  venue = {KU},
  topic = {applications}
}