Preprints
- Rethinking Explainability as a Dialogue: A Practitioner's Perspective
- Himabindu Lakkaraju, Dylan Slack, Yuxin Chen, Chenhao Tan, Sameer Singh
- Preprint, arXiv:2202.01875, 2022
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- Learning Representation for Bayesian Optimization with Collision-free Regularization
- Fengxue Zhang, Brian Nord, Yuxin Chen
- Preprint, arXiv:2203.08656, 2022
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- BALanCe: Deep Bayesian Active Learning via Equivalence Class Annealing
- Renyu Zhang, Aly A Khan, Robert L Grossman, Yuxin Chen
- Preprint, arXiv:2112.13737, 2021
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- Online Learning of Energy Consumption for Navigation of Electric Vehicles
- Niklas Åkerblom, Yuxin Chen, Morteza Haghir Chehreghani
- Preprint, arXiv:2111.02314, 2021 (extended version of IJCAI'20 paper)
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- 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)
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- 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
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- 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
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- Average-case Complexity of Teaching Convex Polytopes via Halfspace Queries
- Akash Kumar, Adish Singla, Yisong Yue, Yuxin Chen
- Preprint, arXiv:2006.14677, 2020
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Publications
- 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
- In North American Chapter of the Association for Computational Linguistics (NAACL), July 2022.
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- Teaching an Active Learner with Contrastive Examples
- Chaoqi Wang, Adish Singla, Yuxin Chen
- In the 35nd Conference on Neural Information Processing Systems (NeurIPS), December 2021.
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- Teaching via Best-Case Counterexamples in the Learning-with-Equivalence-Queries Paradigm
- Akash Kumar, Yuxin Chen, Adish Singla
- In the 35nd Conference on Neural Information Processing Systems (NeurIPS), December 2021.
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- Understanding the Effect of Bias in Deep Anomaly Detection
- Ziyu Ye, Yuxin Chen, Haitao Zheng
- In the 30th International Joint Conference on Artificial Intelligence (IJCAI), Virtual, August 2021.
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- Learning to Make Decisions via Submodular Regularization
- Ayya Alieva, Aiden Aceves, Jialin Song, Stephen Mayo, Yisong Yue, Yuxin Chen
- In the International Conference on Learning Representations (ICLR), May 2021
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[poster]
- The Teaching Dimension of Kernel Perceptron
- Akash Kumar, Hanqi Zhang, Adish Singla, Yuxin Chen
- In the 24th International Conference on Artificial Intelligence and Statistics (AISTATS), April 2021.
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- Adaptive Teaching of Temporal Logic Formulas to Learners with Preferences
- Zhe Xu, Yuxin Chen, Ufuk Topcu
- In the 35th AAAI Conference on Artificial Intelligence (AAAI), February 2021
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- 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
- In IEEE Conference on Lasers and Electro-Optics (CLEO), May 2020.
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- Understanding the Power and Limitations of Teaching with Imperfect Knowledge
- Rati Devidze, Farnam Mansouri, Luis Haug, Yuxin Chen, Adish Singla
- In the 29th International Joint Conference on Artificial Intelligence (IJCAI), Virtual, 2020.
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- An Online Learning Framework for Energy-Efficient Navigation of Electric Vehicles
- Niklas Åkerblom, Yuxin Chen, Morteza Haghir Chehreghani
- In the 29th International Joint Conference on Artificial Intelligence (IJCAI), Virtual, 2020.
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- Preference-Based Batch and Sequential Teaching: Towards a Unified View of Models
- Farnam Mansouri, Yuxin Chen, Ara Vartanian, Xiaojin Zhu, Adish Singla
- In the 33nd Conference on Neural Information Processing Systems (NeurIPS), Vancouver, Canada, December 2019.
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- Landmark Ordinal Embedding
- Nikhil Ghosh, Yuxin Chen, Yisong Yue
- In the 33nd Conference on Neural Information Processing Systems (NeurIPS), Vancouver, Canada, December 2019.
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- Teaching Multiple Concepts to Forgetful Learners
- Anette Hunziker, Yuxin Chen, Oisin Mac Aodha, Manuel Gomez Rodriguez, Andreas Krause, Pietro Perona, Yisong Yue, Adish Singla.
- In the 33nd Conference on Neural Information Processing Systems (NeurIPS), Vancouver, Canada, December 2019.
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- 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.
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- 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
- In the IEEE International Conference on Prognostics and Health Management (ICPHM), San Francisco, USA, June 2019.
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- Batched Stochastic Bayesian Optimization via Combinatorial Constraints Design
- Kevin Yang, Yuxin Chen, Alycia Lee, Yisong Yue
- In the 22th International Conference on Artificial Intelligence and Statistics (AISTATS), Naha, Okinawa, Japan, April 2019.
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- A General Framework for Multi-fidelity Bayesian Optimization with Gaussian Processes
- Jialin Song, Yuxin Chen, Yisong Yue
- In the 22th International Conference on Artificial Intelligence and Statistics (AISTATS), Naha, Okinawa, Japan, April 2019.
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- Barrier Certificates for Assured Machine Teaching
- Mohamadreza Ahmadi, Bo Wu, Yuxin Chen, Yisong Yue, Ufuk Topcu
- In the American Control Conference (ACC), Philadelphia, July 2019
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- 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.
- In the 32nd Conference on Neural Information Processing Systems (NeurIPS), Montreal, Canada, December 2018.
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Teaching Categories to Human Learners with Visual Explanations
- Oisin Mac Aodha, Shihan Su, Yuxin Chen, Pietro Perona, and Yisong Yue.
- In the Conference on Computer Vision and Pattern Recognition (CVPR), Salt Lake City, UT, April 2018.
- Spotlight Presentation
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Near-Optimal Machine Teaching via Explanatory Teaching Sets
- Yuxin Chen, Oisin Mac Aodha, Shihan Su, Pietro Perona, Yisong Yue.
- In the 21th International Conference on Artificial Intelligence and Statistics (AISTATS) , Playa Blanca, Lanzarote, Canary Islands, April 2018.
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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.
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Efficient Online Learning for Optimizing Value of Information: Theory and Application to Interactive Troubleshooting
- Yuxin Chen, Jean-Michel Renders, Morteza Haghir Chehreghani, Andreas Krause.
- In the 33rd Conference on Uncertainty in Artificial Intelligence (UAI), Sydney, Australia, August 2017.
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- Near-optimal Bayesian Active Learning with Correlated and Noisy Tests
- Yuxin Chen, Hamed Hassani, Andreas Krause.
- In the 20th 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
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- 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.
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- 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.
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- Submodular Surrogates for Value of Information
- Yuxin Chen, Shervin Javdani, Amin Karbasi, Drew Bagnell, Siddhartha Srinivasa, Andreas Krause.
- In the 29th AAAI Conference on Artificial Intelligence (AAAI) , Austin, TX, January 2015.
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- Near-Optimal Bayesian Active Learning for Decision Making
- Shervin Javdani, Yuxin Chen, Amin Karbasi, Andreas Krause, Drew Bagnell, Siddhartha Srinivasa.
- In the 17th International Conference on Artificial Intelligence and Statistics (AISTATS) , Reykjavik, Iceland, 2014.
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- Active Detection via Adaptive Submodularity
- Yuxin Chen, Hiroaki Shioi, Cesar Antonio Fuentes Montesinos, Lian Pin Koh, Serge Wich, Andreas Krause.
- In the 31th International Conference on Machine Learning (ICML), Beijing, China, June 2014.
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- 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.
- In IEEE Transactions on Knowledge and Data Engineering (TKDE), October 2013.
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- Near-optimal Batch Mode Active Learning and Adaptive Submodular Optimization.
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.
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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.
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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.
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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.
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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.
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Workshop Contribution
- 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.
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- 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.
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- 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.
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- Batched Stochastic Bayesian Optimization via Combinatorial Constraints Design.
- Kevin Yang, Yuxin Chen, Alycia Lee, Yisong Yue
- NeurIPS Workshop on Machine Learning for Molecules and Materials, Montreal, Canada, December 2018.
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- 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
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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.
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- 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
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- Submodular Surrogates for Value of Information
- Yuxin Chen, Shervin Javdani, Amin Karbasi, Drew Bagnell, Siddhartha Srinivasa, Andreas Krause.
- NeurIPS Workshop on Discrete Optimization in Machine Learning (DISCML), 2014, December 2014.
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- 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 (RSS), July 2014.
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- Active Detection for Biodiversity Monitoring via Adaptive Submodularity.
- Yuxin Chen, Hiroaki Shioi, Cesar Antonio Fuentes Montesinos, Lian Pin Koh, Serge Wich, Andreas Krause.
- NeurIPS Workshop on Machine Learning for Sustainability (MLSUST), Lake Tahoe, NV, December 2013.
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- Near-optimal Batch Mode Active Learning and Stochastic Optimization.
- Yuxin Chen, Andreas Krause.
- NeurIPS Workshop on Discrete Optimization in Machine Learning (DISCML), 2012, December 2012.
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Theses
- Near-optimal Adaptive Information Acquisition: Theory and Applications
- Yuxin Chen. PhD Thesis, ETH Zurich, February 2017.
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[doi]
[pdf] (A5 print)
- Understanding User Intentions in Vertical Image Search
- Yuxin Chen. Master Thesis, The University of Kansas, August 2011.
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[url]
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Patents
- Dynamic Resampling for Sequential Diagnosis and Decision Making
- Jean-Michel Renders, Yuxin Chen
- US Patent App. US20180218264A1, August, 2018.
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Method of Trip Prediction by Leveraging Trip Histories from Neighboring Users
- Morteza Haghir Chehreghani, Yuxin Chen.
- US Patent App. US20180012141, January 2018.
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