Yuxin Chen - Publications

Preprints

• 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)
• [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]

Publications

• 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.
• [pdf]


• 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.
• (pdf forthcoming)


• 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.
• [pdf]


• 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
• [pdf] [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.
• [pdf]


• 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
• [pdf]


• 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.
• [url]


• 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.
• [bibtex] [pdf]


• 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.
• [bibtex] [pdf]


• 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.
• [bibtex] [pdf] [poster]


• Landmark Ordinal Embedding
• Nikhil Ghosh, Yuxin Chen, Yisong Yue
• In the 33nd Conference on 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.
• In the 33nd Conference on 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
• In the 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
• In the 22th International Conference on Artificial Intelligence and Statistics (AISTATS), Naha, Okinawa, Japan, April 2019.
• [bibtex] [pdf] [poster]


• 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.
• [bibtex] [pdf] [poster]


• 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
• [bibtex] [pdf]


• 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.
• [bibtex] [pdf] [poster]


• 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
• [bibtex] [pdf]


• 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.
• [bibtex] [pdf] [long] [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.
• In the 33rd 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.
• 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
• [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]


• 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.
• [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.
• In the 17th International Conference on Artificial Intelligence and Statistics (AISTATS) , Reykjavik, Iceland, 2014.
• [bibtex] [pdf] [long version]


• 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.
• [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.
• In 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.
  • In the 30th International Conference on Machine Learning (ICML), Atlanta, GA, June 2013.
  • [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]

Workshop Contribution

• 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]


• 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.
• [bibtex]


• 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]


• 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 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.
• NeurIPS Workshop on Discrete Optimization in Machine Learning (DISCML), 2014, December 2014.
• [poster]


• 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.
• [pdf] [talk]


• 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.
• [poster]


• 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.
• [pdf] [poster]

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]

Patents

• Dynamic Resampling for Sequential Diagnosis and Decision Making
• Jean-Michel Renders, Yuxin Chen
• US Patent App. US20180218264A1, August, 2018.
• [bibtex] [link]


• Method of Trip Prediction by Leveraging Trip Histories from Neighboring Users
• Morteza Haghir Chehreghani, Yuxin Chen.
• US Patent App. US20180012141, January 2018.
• [bibtex] [link]