Yuxin Chen - Publications

Publications

2025

• Finding Interior Optimum of Black-box Constrained Objective with Bayesian Optimization
• Fengxue Zhang, Yuxin Chen
• Conference on Uncertainty in Artificial Intelligence (UAI), July 2025.
• Preliminary version appeared in the NeurIPS Workshop on Bayesian Decision-making and Uncertainty (BDU), December 2024.
• [pdf]


• Bayesian Optimization with Inexact Acquisition: Is Random Grid Search Sufficient?
• Hwanwoo Kim, Chong Liu, Yuxin Chen
• Conference on Uncertainty in Artificial Intelligence (UAI), July 2025.
• [pdf]


• 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.
• Accepted to Science Advances, April 2025.
• [preprint]


• 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.
• Molecular Systems Design & Engineering (MSDE), March 2025.
• Selected as MSDE Recent HOT Article
• [url]


• Constrained Multi-objective Bayesian Optimization
• Diantong Li, Fengxue Zhang, Chong Liu, Yuxin Chen
• International Conference on Artificial Intelligence and Statistics (AISTATS), May 2025.
• Preliminary version appeard in the NeurIPS Workshop on Bayesian Decision-making and Uncertainty (BDU), December 2024.
• [workshop version]


• Robust Multi-fidelity Bayesian Optimization with Deep Kernel and Partition
• Fengxue Zhang, Thomas Desautels, Yuxin Chen
• International Conference on Artificial Intelligence and Statistics (AISTATS), May 2025.
• Preliminary version appeard in the NeurIPS Workshop on Bayesian Decision-making and Uncertainty (BDU), December 2024.
• [workshop version]

2024

• Contextual Active Model Selection
• Xuefeng Liu, Fangfang Xia, Rick L. Stevens, Yuxin Chen
• Neural Information Processing Systems (NeurIPS), December 2024.
• Preliminary version appeard in the ICML Workshop on Adaptive Experimental Design and Active Learning in the Real World (ReALML), July 2022.
• [pdf] [workshop poster]


• Active Learning for Optimal Minimization of Experimental Characterization Uncertainty
• Marcus Schwarting, Nathan Seifert, Logan Ward, Ben Blaiszik, Ian Foster, Yuxin Chen, Kirill Prozument
• NeurIPS Workshop on Bayesian Decision-making and Uncertainty (BDU), December 2024.
• [pdf]


• Direct Acquisition Optimization for Low-Budget Active Learning
• Zhuokai Zhao, Yibo Jiang, Yuxin Chen
• NeurIPS Workshop on Bayesian Decision-making and Uncertainty (BDU), December 2024.
• Lightning talk
• [pdf]


• 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 Workshop on Mathematical Reasoning and AI (Math-AI), December 2024.
• [pdf]


• 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
• Featured as inside front cover
• Chemical Society Reviews, December 2024.
• [url]


• 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 Sustainable Resource Management, November 2024.
• [url]


• No-Regret Learning of Nash Equilibrium for Black-Box Games via Gaussian Processes
• Minbiao Han^*, Fengxue Zhang^*, Yuxin Chen
• Conference on Uncertainty in Artificial Intelligence (UAI), July 2024.
• [pdf] [poster]


• Learning to Rank for Active Learning via Multi-Task Bilevel Optimization
• Zixin Ding, Si Chen, Ruoxi Jia, Yuxin Chen
• Conference on Uncertainty in Artificial Intelligence (UAI), July 2024.
• [pdf] [DMLR poster] [UAI poster]


• Model-based Policy Optimization under Approximate Bayesian Inference
• Chaoqi Wang, Yuxin Chen, Kevin Murphy
• International Conference on Artificial Intelligence and Statistics (AISTATS), May 2024.
• Oral presentation
• Preliminary version appeard in the ICML Workshop on New Frontiers in Learning, Control, and Dynamical Systems, 2023
• [pdf] [webpage]


• Don't Be Pessimistic Too Early: Look K Steps Ahead!
• Chaoqi Wang, Ziyu Ye, Kevin Murphy, Yuxin Chen
• International Conference on Artificial Intelligence and Statistics (AISTATS), May 2024.
• [pdf]


• Blending Imitation and Reinforcement Learning for Robust Policy Improvement
• Xuefeng Liu, Takuma Yoneda, Rick Stevens, Matthew Walter, Yuxin Chen
• International Conference on Learning Representations (ICLR), May 2024
• Spotlight presentation
• [pdf] [website]


• Beyond Reverse KL: Generalizing Direct Preference Optimization with Diverse Divergence Constraints
• Chaoqi Wang, Yibo Jiang, Chenghao Yang, Han Liu, Yuxin Chen
• International Conference on Learning Representations (ICLR), May 2024
• Spotlight presentation
• Preliminary version appeard in the NeurIPS Workshop on Socially Responsible Language Modelling Research, December 2023
• [pdf] [poster] [code]


• Enhancing Instance-Level Image Classification with Set-Level Labels
• Renyu Zhang, Aly A. Khan, Yuxin Chen, Robert L. Grossman
• International Conference on Learning Representations (ICLR), May 2024
• Preliminary version appeard in the Medical Imaging meets NeurIPS Workshop, December 2023.
• [pdf] [poster]

2023

• Efficient Online Decision Tree Learning with Active Feature Acquisition
• Arman Rahbar, Ziyu Ye, Yuxin Chen, and Morteza Haghir Chehreghani
• International Joint Conference on Artificial Intelligence (IJCAI), Macau, August 2023
• [pdf]


• Active Policy Improvement from Multiple Black-box Oracles
• Xuefeng Liu, Takuma Yoneda, Chaoqi Wang, Matthew Walter, Yuxin Chen
• International Conference on Machine Learning (ICML), Hawaii, July 2023
• [pdf] [poster] [code]


• 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
• International Conference on Machine Learning (ICML), Hawaii, July 2023.
• [pdf]


• Iterative Machine Teaching for Black-box Markov Learners
• Chaoqi Wang, Sandra Zilles, Adish Singla, Yuxin Chen
• ICML Workshop on Theory of Mind (ToM), 2023
• [pdf]


• Scalable Batch-Mode Deep Bayesian Active Learning via Equivalence Class Annealing
• Renyu Zhang, Aly A Khan, Robert L Grossman, Yuxin Chen
• International Conference on Learning Representations (ICLR), May 2023
• [pdf] [poster]


• Learning Human-Compatible Representations for Case-Based Decision Support
• Han Liu, Yizhou Tian, Chacha Chen, Shi Feng, Yuxin Chen, Chenhao Tan
• International Conference on Learning Representations (ICLR), May 2023
• [pdf]


• Online Learning of Energy Consumption for Navigation of Electric Vehicles
• Niklas Åkerblom, Yuxin Chen, Morteza Haghir Chehreghani
• Journal of Artificial Intelligence (AIJ), 2023 (extended version of IJCAI'20 paper)
• [pdf]

2022

• Trip Prediction by Leveraging Trip Histories from Neighboring Users
• Yuxin Chen, Morteza Haghir Chehreghani
• IEEE International Conference on Intelligent Transportation Systems (ITSC), October 2022.
• [pdf]


• 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
• North American Chapter of the Association for Computational Linguistics (NAACL), July 2022.
• [paper] [code]


• Contextual Active Online Model Selection with Expert Advice
• Xuefeng Liu, Fangfang Xia, Rick L. Stevens, Yuxin Chen
• ICML Workshop on Adaptive Experimental Design and Active Learning in the Real World (ReALML), July, 2022.
• [pdf] [poster]


• Class-wise Thresholding for Detecting Out-of-Distribution Data.
• Matteo Guarrera, Baihong Jin, Tung-Wei Lin, Maria Zuluaga, Yuxin Chen, Alberto Sangiovanni-Vincentelli
• CVPR Workshop on Fair, Data-Efficient, and Trusted Computer Vision (TCV), June, 2022.
• [pdf]


• The Price of Sparsity: Generalization and Memorization in Sparse Neural Network
• Ziyu Ye, Chaoqi Wang, Zixin Ding, Yuxin Chen
• Sparsity in Neural Networks Workshop (SNN), July, 2022.
• [paper] [poster]

2021

• Teaching an Active Learner with Contrastive Examples
• Chaoqi Wang, Adish Singla, Yuxin Chen
• Neural Information Processing Systems (NeurIPS), December 2021.
• [bibtex] [pdf]


• Teaching via Best-Case Counterexamples in the Learning-with-Equivalence-Queries Paradigm
• Akash Kumar, Yuxin Chen, Adish Singla
• Neural Information Processing Systems (NeurIPS), December 2021.
• [bibtex] [pdf] [poster]


• Understanding the Effect of Bias in Deep Anomaly Detection
• Ziyu Ye, Yuxin Chen, Haitao Zheng
• International Joint Conference on Artificial Intelligence (IJCAI), Virtual, August 2021.
• [pdf] [poster]


• Learning to Make Decisions via Submodular Regularization
• Ayya Alieva, Aiden Aceves, Jialin Song, Stephen Mayo, Yisong Yue, Yuxin Chen
• International Conference on Learning Representations (ICLR), May 2021
• [pdf] [poster]


• The Teaching Dimension of Kernel Perceptron
• Akash Kumar, Hanqi Zhang, Adish Singla, Yuxin Chen
• International Conference on Artificial Intelligence and Statistics (AISTATS), April 2021.
• [pdf] [poster]


• Adaptive Teaching of Temporal Logic Formulas to Learners with Preferences
• Zhe Xu, Yuxin Chen, Ufuk Topcu
• AAAI Conference on Artificial Intelligence (AAAI), February 2021
• [pdf]

2020

• 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
• IEEE Conference on Lasers and Electro-Optics (CLEO), May 2020.
• [url]


• Understanding the Power and Limitations of Teaching with Imperfect Knowledge
• Rati Devidze, Farnam Mansouri, Luis Haug, Yuxin Chen, Adish Singla
• International Joint Conference on Artificial Intelligence (IJCAI), Virtual, 2020.
• [bibtex] [pdf]


• An Online Learning Framework for Energy-Efficient Navigation of Electric Vehicles
• Niklas Åkerblom, Yuxin Chen, Morteza Haghir Chehreghani
• International Joint Conference on Artificial Intelligence (IJCAI), Virtual, 2020.
• [bibtex] [pdf] [extended version]


• Design of Physical Experiments via Collision-Free Latent Space Optimization.
• Fengxue Zhang, Yair Altas, Louise Fan, Kaustubh Vinchure, Brian Nord, Yuxin Chen
• NeurIPS Workshop on Machine Learning and the Physical Sciences, December 2020.
• [bibtex] [pdf] [poster]


• Towards an Interpretable Data-driven Trigger System for High-throughput Physics Facilities.
• Chinmaya Mahesh, Kristin Dona, David W. Miller, Yuxin Chen
• NeurIPS Workshop on Machine Learning and the Physical Sciences, December 2020.
• [bibtex] [pdf] [poster]

2019

• Preference-Based Batch and Sequential Teaching: Towards a Unified View of Models
• Farnam Mansouri, Yuxin Chen, Ara Vartanian, Xiaojin Zhu, Adish Singla
• Neural Information Processing Systems (NeurIPS), Vancouver, Canada, December 2019.
• [bibtex] [pdf] [poster]


• Landmark Ordinal Embedding
• Nikhil Ghosh, Yuxin Chen, Yisong Yue
• Neural Information Processing Systems (NeurIPS), Vancouver, Canada, December 2019.
• [bibtex] [pdf] [poster]


• Teaching Multiple Concepts to Forgetful Learners
• Anette Hunziker, Yuxin Chen, Oisin Mac Aodha, Manuel Gomez Rodriguez, Andreas Krause, Pietro Perona, Yisong Yue, Adish Singla.
• Neural Information Processing Systems (NeurIPS), Vancouver, Canada, December 2019.
• [bibtex] [pdf] [poster]


• 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
• IEEE International Conference on Machine Learning and Applications (ICMLA), Boca Raton, USA, December 2019.
• [pdf]


• 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
• IEEE International Conference on Prognostics and Health Management (ICPHM), San Francisco, USA, June 2019.
• [pdf]


• Batched Stochastic Bayesian Optimization via Combinatorial Constraints Design
• Kevin Yang, Yuxin Chen, Alycia Lee, Yisong Yue
• International Conference on Artificial Intelligence and Statistics (AISTATS), Naha, Okinawa, Japan, April 2019.
• NeurIPS Workshop on Machine Learning for Molecules and Materials, Montreal, Canada, December 2018.
• [bibtex] [pdf] [poster]


• A General Framework for Multi-fidelity Bayesian Optimization with Gaussian Processes
• Jialin Song, Yuxin Chen, Yisong Yue
• International Conference on Artificial Intelligence and Statistics (AISTATS), Naha, Okinawa, Japan, April 2019.
• [bibtex] [pdf] [poster]


• Barrier Certificates for Assured Machine Teaching
• Mohamadreza Ahmadi, Bo Wu, Yuxin Chen, Yisong Yue, Ufuk Topcu
• American Control Conference (ACC), Philadelphia, July 2019
• [bibtex] [pdf]

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.
• Neural Information Processing Systems (NeurIPS), Montreal, Canada, December 2018.
• [bibtex] [pdf] [poster]


• 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 Workshop on Machine Learning for Molecules and Materials, Montreal, Canada, December 2018
• [bibtex]


• Teaching Categories to Human Learners with Visual Explanations
• Oisin Mac Aodha, Shihan Su, Yuxin Chen, Pietro Perona, and Yisong Yue.
• Conference on Computer Vision and Pattern Recognition (CVPR), Salt Lake City, UT, April 2018.
• Spotlight presentation
• [bibtex] [pdf]


• Near-Optimal Machine Teaching via Explanatory Teaching Sets
• Yuxin Chen, Oisin Mac Aodha, Shihan Su, Pietro Perona, Yisong Yue.
• International Conference on Artificial Intelligence and Statistics (AISTATS) , Playa Blanca, Lanzarote, Canary Islands, April 2018.
• [bibtex] [pdf] [long] [poster]

Before 2017

• Interpretable Machine Teaching via Feature Feedback
• Shihan Su, Yuxin Chen, Oisin Mac Aodha, Pietro Perona, Yisong Yue
• NeurIPS Workshop on Teaching Machines, Robots, and Humans, December 2017.
• [bibtex] [pdf] [poster]


• Learning Shape Analysis
• Marc Brockschmidt, Yuxin Chen, Pushmeet Kohli, Siddharth Krishna, Daniel Tarlow.
• In the 24th Static Analysis Symposium (SAS), New York City, NY, August 2017.
• [bibtex] [pdf] [doi]


• Efficient Online Learning for Optimizing Value of Information: Theory and Application to Interactive Troubleshooting
• Yuxin Chen, Jean-Michel Renders, Morteza Haghir Chehreghani, Andreas Krause.
• Conference on Uncertainty in Artificial Intelligence (UAI), Sydney, Australia, August 2017.
• [bibtex] [pdf] [poster]


• Near-optimal Bayesian Active Learning with Correlated and Noisy Tests
• Yuxin Chen, Hamed Hassani, Andreas Krause.
• International Conference on Artificial Intelligence and Statistics (AISTATS) , Fort Lauderdale, FL, April 2017.
• Oral presentation
• Extended version published in the Electronic Journal of Statistics (EJS), Volume 11, 2017
• [bibtex] [pdf] [long] [journal] [poster]


• Learning to Verify the Heap
• Marc Brockschmidt, Yuxin Chen, Byron Cook, Pushmeet Kohli, Siddharth Krishna, Daniel Tarlow, He Zhu.
• Technical report, MSR-TR-2016-17, June 2016.
• [bibtex] [pdf] [poster]


• Sequential Information Maximization: When is Greedy Near-optimal?
• Yuxin Chen, Hamed Hassani, Amin Karbasi, Andreas Krause.
• In the 28th Annual Conference on Learning Theory (COLT) , Paris, France, July 2015.
• [bibtex] [pdf] [poster] [talk]


• Learning to Decipher the Heap for Program Verification.
• Marc Brockschmidt, Yuxin Chen, Byron Cook, Pushmeet Kohli, Daniel Tarlow.
• ICML Workshop on Constructive Machine Learning (CML), Lille, France, July 2015.
• Winner of the Best Paper Award
• [pdf]


• Submodular Surrogates for Value of Information
• Yuxin Chen, Shervin Javdani, Amin Karbasi, Drew Bagnell, Siddhartha Srinivasa, Andreas Krause.
• AAAI Conference on Artificial Intelligence (AAAI) , Austin, TX, January 2015.
• NeurIPS Workshop on Discrete Optimization in Machine Learning (DISCML), 2014, December 2014.
• [bibtex] [pdf] [long version] [poster]


• Near-Optimal Bayesian Active Learning for Decision Making
• Shervin Javdani, Yuxin Chen, Amin Karbasi, Andreas Krause, Drew Bagnell, Siddhartha Srinivasa.
• International Conference on Artificial Intelligence and Statistics (AISTATS) , Reykjavik, Iceland, 2014.
• [bibtex] [pdf] [long version]


• Decision Region Determination for Touch Based Localization
• Shervin Javdani, Yuxin Chen, Amin Karbasi, Drew Bagnell, Siddhartha Srinivasa, Andreas Krause.
• RSS Workshop on Information-based Grasp and Manipulation Planning, July 2014.
• [pdf] [talk]


• Active Detection via Adaptive Submodularity
• Yuxin Chen, Hiroaki Shioi, Cesar Antonio Fuentes Montesinos, Lian Pin Koh, Serge Wich, Andreas Krause.
• International Conference on Machine Learning (ICML), Beijing, China, June 2014.
• NeurIPS Workshop on Machine Learning for Sustainability (MLSUST), Lake Tahoe, NV, December 2013.
• [bibtex] [pdf] [long version] [poster] [talk]


• iLike: Bridging the Semantic Gap in Vertical Image Search by Integrating Text and Visual Features.
• Yuxin Chen, Hariprasad Sampathkumar, Bo Luo, and Xue-wen Chen.
• IEEE Transactions on Knowledge and Data Engineering (TKDE), October 2013.
• [bibtex] [link] [doi]


• Near-optimal Batch Mode Active Learning and Adaptive Submodular Optimization.
  • Yuxin Chen, Andreas Krause.
  • International Conference on Machine Learning (ICML), Atlanta, GA, June 2013.
  • NeurIPS Workshop on Discrete Optimization in Machine Learning (DISCML), 2012, December 2012.
  • [bibtex] [pdf] [long version] [spotlight] [poster] [talk]
  
  
• IPKB: A Digital Library for Invertebrate Paleontology.
• Yuanliang Meng, Junyan Li, Patrick Denton, Yuxin Chen, Bo Luo, Paul Selden, Xue-wen Chen.
• In the 12th ACM/IEEE - CS Joint Conference on Digital Libraries (JCDL), Washington DC, June 2012.
• [bibtex] [pdf] [doi]


• S2A: Secure Smart Household Appliances.
• Yuxin Chen and Bo Luo.
• In the 2nd ACM Conf. on Data and Application Security and Privacy (CODASPY), San Antonio, TX, 2012.
• [bibtex] [link] [doi]


• Cephalometric Landmark Tracing Using Deformable Templates.
• Yuxin Chen, Brian Potetz, Bo Luo and Xue-wen Chen.
• In Proceedings of the 1st IEEE Conference on Healthcare Informatics, Imaging, and Systems Biology (HISB), San Jose, CA, July 2011.
• [bibtex] [link] [slides] [doi]


• Privacy-Preserving Group Linkage.
• Fengjun Li, Yuxin Chen, Bo Luo, Dongwon Lee and Peng Liu.
• In the 23rd Scientic and Statistical Database Management Conference (SSDBM), Portland, OR, July 2011.
• [bibtex] [pdf] [slides] [doi]


• iLike: Integrating Visual and Textual Features for Vertical Search.
• Yuxin Chen, Nenghai Yu, Bo Luo, and Xue-wen Chen.
• Full Paper in ACM Multimedia Conference (ACMMM), Firenze, Italy, October 2010.
• [bibtex] [pdf] [slides] [doi]

Preprints

• Constrained Bayesian Optimization with Adaptive Active Learning of Unknown Constraints
• Fengxue Zhang, Zejie Zhu, Yuxin Chen
• Preprint, arXiv:2310.08751, 2023
• [pdf]


• Rethinking Explainability as a Dialogue: A Practitioner's Perspective
• Himabindu Lakkaraju, Dylan Slack, Yuxin Chen, Chenhao Tan, Sameer Singh
• Preprint, arXiv:2202.01875, 2022
• [pdf]


• Learning Representation for Bayesian Optimization with Collision-free Regularization
• Fengxue Zhang, Brian Nord, Yuxin Chen
• Preprint, arXiv:2203.08656, 2022
• [pdf]


• Preference-Based Batch and Sequential Teaching
• Farnam Mansouri, Yuxin Chen, Ara Vartanian, Xiaojin Zhu, Adish Singla
• Preprint, arXiv:2010.10012, 2020 (extended version of NeurIPS'19 paper)
• [pdf]


• 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
• [pdf]


• 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
• [pdf]


• Average-case Complexity of Teaching Convex Polytopes via Halfspace Queries
• Akash Kumar, Adish Singla, Yisong Yue, Yuxin Chen
• Preprint, arXiv:2006.14677, 2020
• [pdf]

Theses

• Near-optimal Adaptive Information Acquisition: Theory and Applications
• Yuxin Chen. PhD Thesis, ETH Zurich, February 2017.
• [doi] [pdf] (A5 print)


• Understanding User Intentions in Vertical Image Search
• Yuxin Chen. Master Thesis, The University of Kansas, August 2011.
• [url] [pdf]