Yuxin Chen

Publication Activity (10 Years)

Years Active: 2010-2024
Publications (10 Years): 69

Top Topics

Change Point Detection

Gaussian Processes

Top Venues

Publications

Renyu Zhang, Aly A. Khan, Yuxin Chen, Robert L. Grossman
Enhancing Instance-Level Image Classification with Set-Level Labels. ICLR (2024)
Chaoqi Wang, Yuxin Chen, Kevin Murphy
Model-based Policy Optimization under Approximate Bayesian Inference. AISTATS (2024)
Xuefeng Liu, Takuma Yoneda, Rick Stevens, Matthew R. Walter, Yuxin Chen
Blending Imitation and Reinforcement Learning for Robust Policy Improvement. ICLR (2024)
Minbiao Han, Fengxue Zhang, Yuxin Chen
No-Regret Learning of Nash Equilibrium for Black-Box Games via Gaussian Processes. CoRR (2024)
Chaoqi Wang, Ziyu Ye, Kevin Murphy, Yuxin Chen
Don't Be Pessimistic Too Early: Look K Steps Ahead! AISTATS (2024)
Renyu Zhang, Aly A. Khan, Yuxin Chen, Robert L. Grossman
Enhancing Instance-Level Image Classification with Set-Level Labels. CoRR (2023)
Arman Rahbar, Ziyu Ye, Yuxin Chen, Morteza Haghir Chehreghani
Efficient Online Decision Tree Learning with Active Feature Acquisition. CoRR (2023)
Fengxue Zhang, Zejie Zhu, Yuxin Chen
Constrained Bayesian Optimization with Adaptive Active Learning of Unknown Constraints. CoRR (2023)
Renyu Zhang, Aly A. Khan, Robert L. Grossman, Yuxin Chen
Scalable Batch-Mode Deep Bayesian Active Learning via Equivalence Class Annealing. ICLR (2023)
Chaoqi Wang, Yibo Jiang, Chenghao Yang, Han Liu, Yuxin Chen
Beyond Reverse KL: Generalizing Direct Preference Optimization with Diverse Divergence Constraints. CoRR (2023)
Arman Rahbar, Ziyu Ye, Yuxin Chen, Morteza Haghir Chehreghani
Efficient Online Decision Tree Learning with Active Feature Acquisition. IJCAI (2023)
Xuefeng Liu, Takuma Yoneda, Rick L. Stevens, Matthew R. Walter, Yuxin Chen
Blending Imitation and Reinforcement Learning for Robust Policy Improvement. CoRR (2023)
Xuefeng Liu, Takuma Yoneda, Chaoqi Wang, Matthew R. Walter, Yuxin Chen
Active Policy Improvement from Multiple Black-box Oracles. ICML (2023)
Xuefeng Liu, Takuma Yoneda, Chaoqi Wang, Matthew R. Walter, Yuxin Chen
Active Policy Improvement from Multiple Black-box Oracles. CoRR (2023)
Fengxue Zhang, Jialin Song, James C. Bowden, Alexander Ladd, Yisong Yue, Thomas A. Desautels, Yuxin Chen
Learning Regions of Interest for Bayesian Optimization with Adaptive Level-Set Estimation. CoRR (2023)
Zhuolin Yang, Yuxin Chen, Zain Sarwar, Hadleigh Schwartz, Ben Y. Zhao, Haitao Zheng
Towards a General Video-based Keystroke Inference Attack. USENIX Security Symposium (2023)
Niklas Åkerblom, Yuxin Chen, Morteza Haghir Chehreghani
Online learning of energy consumption for navigation of electric vehicles. Artif. Intell. 317 (2023)
Fengxue Zhang, Jialin Song, James C. Bowden, Alexander Ladd, Yisong Yue, Thomas Desautels, Yuxin Chen
Learning Regions of Interest for Bayesian Optimization with Adaptive Level-Set Estimation. ICML (2023)
Matteo Guarrera, Baihong Jin, Tung-Wei Lin, Maria A. Zuluaga, Yuxin Chen, Alberto L. Sangiovanni-Vincentelli
Class-wise Thresholding for Robust Out-of-Distribution Detection. CVPR Workshops (2022)
Yuxin Chen, Morteza Haghir Chehreghani
Trip Prediction by Leveraging Trip Histories from Neighboring Users. ITSC (2022)
Chaoqi Wang, Adish Singla, Yuxin Chen
Teaching an Active Learner with Contrastive Examples. CoRR (2021)
Akash Kumar, Yuxin Chen, Adish Singla
Teaching via Best-Case Counterexamples in the Learning-with-Equivalence-Queries Paradigm. NeurIPS (2021)
Niklas Åkerblom, Yuxin Chen, Morteza Haghir Chehreghani
Online Learning of Energy Consumption for Navigation of Electric Vehicles. CoRR (2021)
Zhe Xu, Yuxin Chen, Ufuk Topcu
Adaptive Teaching of Temporal Logic Formulas to Preference-based Learners. AAAI (2021)
Akash Kumar, Hanqi Zhang, Adish Singla, Yuxin Chen
The Teaching Dimension of Kernel Perceptron. AISTATS (2021)
Chaoqi Wang, Adish Singla, Yuxin Chen
Teaching an Active Learner with Contrastive Examples. NeurIPS (2021)
Matteo Guarrera, Baihong Jin, Tung-Wei Lin, Maria Zuluaga, Yuxin Chen, Alberto L. Sangiovanni-Vincentelli
Class-wise Thresholding for Detecting Out-of-Distribution Data. CoRR (2021)
Ayya Alieva, Aiden Aceves, Jialin Song, Stephen Mayo, Yisong Yue, Yuxin Chen
Learning to Make Decisions via Submodular Regularization. ICLR (2021)
Rati Devidze, Farnam Mansouri, Luis Haug, Yuxin Chen, Adish Singla
Understanding the Power and Limitations of Teaching with Imperfect Knowledge. CoRR (2020)
Farnam Mansouri, Yuxin Chen, Ara Vartanian, Xiaojin Zhu, Adish Singla
Preference-Based Batch and Sequential Teaching. CoRR (2020)
Baihong Jin, Yingshui Tan, Albert Liu, Xiangyu Yue, Yuxin Chen, Alberto L. Sangiovanni-Vincentelli
Using Ensemble Classifiers to Detect Incipient Anomalies. CoRR (2020)
Rati Devidze, Farnam Mansouri, Luis Haug, Yuxin Chen, Adish Singla
Understanding the Power and Limitations of Teaching with Imperfect Knowledge. IJCAI (2020)
Akash Kumar, Hanqi Zhang, Adish Singla, Yuxin Chen
The Teaching Dimension of Kernel Perceptron. CoRR (2020)
Yingshui Tan, Baihong Jin, Xiangyu Yue, Yuxin Chen, Alberto L. Sangiovanni-Vincentelli
Exploiting Uncertainties from Ensemble Learners to Improve Decision-Making in Healthcare AI. CoRR (2020)
Niklas Åkerblom, Yuxin Chen, Morteza Haghir Chehreghani
An Online Learning Framework for Energy-Efficient Navigation of Electric Vehicles. IJCAI (2020)
Akash Kumar, Adish Singla, Yisong Yue, Yuxin Chen
Average-case Complexity of Teaching Convex Polytopes via Halfspace Queries. CoRR (2020)
Niklas Åkerblom, Yuxin Chen, Morteza Haghir Chehreghani
An Online Learning Framework for Energy-Efficient Navigation of Electric Vehicles. CoRR (2020)
Zhe Xu, Yuxin Chen, Ufuk Topcu
Adaptive Teaching of Temporal Logic Formulas to Learners with Preferences. CoRR (2020)
Baihong Jin, Yingshui Tan, Yuxin Chen, Kameshwar Poolla, Alberto L. Sangiovanni-Vincentelli
Are Ensemble Classifiers Powerful Enough for the Detection and Diagnosis of Intermediate-Severity Faults? CoRR (2020)
Mohamadreza Ahmadi, Bo Wu, Yuxin Chen, Yisong Yue, Ufuk Topcu
Barrier Certificates for Assured Machine Teaching. ACC (2019)
Baihong Jin, Yuxin Chen, Dan Li, Kameshwar Poolla, Alberto L. Sangiovanni-Vincentelli
A One-Class Support Vector Machine Calibration Method for Time Series Change Point Detection. CoRR (2019)
Kevin K. Yang, Yuxin Chen, Alycia Lee, Yisong Yue
Batched Stochastic Bayesian Optimization via Combinatorial Constraints Design. CoRR (2019)
Baihong Jin, Yingshui Tan, Alexander J. Nettekoven, Yuxin Chen, Ufuk Topcu, Yisong Yue, Alberto L. Sangiovanni-Vincentelli
An Encoder-Decoder Based Approach for Anomaly Detection with Application in Additive Manufacturing. CoRR (2019)
Baihong Jin, Yuxin Chen, Dan Li, Kameshwar Poolla, Alberto L. Sangiovanni-Vincentelli
A One-Class Support Vector Machine Calibration Method for Time Series Change Point Detection. ICPHM (2019)
Nikhil Ghosh, Yuxin Chen, Yisong Yue
Landmark Ordinal Embedding. CoRR (2019)
Yingshui Tan, Baihong Jin, Alexander J. Nettekoven, Yuxin Chen, Yisong Yue, Ufuk Topcu, Alberto L. Sangiovanni-Vincentelli
An Encoder-Decoder Based Approach for Anomaly Detection with Application in Additive Manufacturing. ICMLA (2019)
Baihong Jin, Yingshui Tan, Yuxin Chen, Alberto L. Sangiovanni-Vincentelli
Augmenting Monte Carlo Dropout Classification Models with Unsupervised Learning Tasks for Detecting and Diagnosing Out-of-Distribution Faults. CoRR (2019)
Farnam Mansouri, Yuxin Chen, Ara Vartanian, Xiaojin Zhu, Adish Singla
Preference-Based Batch and Sequential Teaching: Towards a Unified View of Models. CoRR (2019)
Kevin K. Yang, Yuxin Chen, Alycia Lee, Yisong Yue
Batched Stochastic Bayesian Optimization via Combinatorial Constraints Design. AISTATS (2019)
Anette Hunziker, Yuxin Chen, Oisin Mac Aodha, Manuel Gomez Rodriguez, Andreas Krause, Pietro Perona, Yisong Yue, Adish Singla
Teaching Multiple Concepts to a Forgetful Learner. NeurIPS (2019)
Nikhil Ghosh, Yuxin Chen, Yisong Yue
Landmark Ordinal Embedding. NeurIPS (2019)
Jialin Song, Yuxin Chen, Yisong Yue
A General Framework for Multi-fidelity Bayesian Optimization with Gaussian Processes. AISTATS (2019)
Farnam Mansouri, Yuxin Chen, Ara Vartanian, Xiaojin (Jerry) Zhu, Adish Singla
Preference-Based Batch and Sequential Teaching: Towards a Unified View of Models. NeurIPS (2019)
Jialin Song, Yuxin Chen, Yisong Yue
A General Framework for Multi-fidelity Bayesian Optimization with Gaussian Processes. CoRR (2018)
Yuxin Chen, Morteza Haghir Chehreghani
Trip Prediction by Leveraging Trip Histories from Neighboring Users. CoRR (2018)
Anette Hunziker, Yuxin Chen, Oisin Mac Aodha, Manuel Gomez-Rodriguez, Andreas Krause, Pietro Perona, Yisong Yue, Adish Singla
Teaching Multiple Concepts to Forgetful Learners. CoRR (2018)
Oisin Mac Aodha, Shihan Su, Yuxin Chen, Pietro Perona, Yisong Yue
Teaching Categories to Human Learners with Visual Explanations. CoRR (2018)
Yuxin Chen, Adish Singla, Oisin Mac Aodha, Pietro Perona, Yisong Yue
Understanding the Role of Adaptivity in Machine Teaching: The Case of Version Space Learners. CoRR (2018)
Oisin Mac Aodha, Shihan Su, Yuxin Chen, Pietro Perona, Yisong Yue
Teaching Categories to Human Learners With Visual Explanations. CVPR (2018)
Jialin Song, Yury S. Tokpanov, Yuxin Chen, Dagny Fleischman, Kate T. Fountaine, Harry A. Atwater, Yisong Yue
Optimizing Photonic Nanostructures via Multi-fidelity Gaussian Processes. CoRR (2018)
Yuxin Chen, Adish Singla, Oisin Mac Aodha, Pietro Perona, Yisong Yue
Understanding the Role of Adaptivity in Machine Teaching: The Case of Version Space Learners. NeurIPS (2018)
Yuxin Chen, Oisin Mac Aodha, Shihan Su, Pietro Perona, Yisong Yue
Near-Optimal Machine Teaching via Explanatory Teaching Sets. AISTATS (2018)
Mohamadreza Ahmadi, Bo Wu, Yuxin Chen, Yisong Yue, Ufuk Topcu
Barrier Certificates for Assured Machine Teaching. CoRR (2018)
Yuxin Chen, Jean-Michel Renders, Morteza Haghir Chehreghani, Andreas Krause
Efficient Online Learning for Optimizing Value of Information: Theory and Application to Interactive Troubleshooting. CoRR (2017)
Yuxin Chen, Seyed Hamed Hassani, Andreas Krause
Near-optimal Bayesian Active Learning with Correlated and Noisy Tests. AISTATS (2017)
Yuxin Chen, Jean-Michel Renders, Morteza Haghir Chehreghani, Andreas Krause
Efficient Online Learning for Optimizing Value of Information: Theory and Application to Interactive Troubleshooting. UAI (2017)
Yuxin Chen, S. Hamed Hassani, Andreas Krause
Near-optimal Bayesian Active Learning with Correlated and Noisy Tests. CoRR (2016)
Yuxin Chen, Shervin Javdani, Amin Karbasi, J. Andrew Bagnell, Siddhartha S. Srinivasa, Andreas Krause
Submodular Surrogates for Value of Information. AAAI (2015)
Yuxin Chen, S. Hamed Hassani, Amin Karbasi, Andreas Krause
Sequential Information Maximization: When is Greedy Near-optimal? COLT (2015)
Yuxin Chen, Hiroaki Shioi, Cesar Fuentes Montesinos, Lian Pin Koh, Serge A. Wich, Andreas Krause
Active Detection via Adaptive Submodularity. ICML (2014)
Shervin Javdani, Yuxin Chen, Amin Karbasi, Andreas Krause, Drew Bagnell, Siddhartha S. Srinivasa
Near Optimal Bayesian Active Learning for Decision Making. AISTATS (2014)
Shervin Javdani, Yuxin Chen, Amin Karbasi, Andreas Krause, J. Andrew Bagnell, Siddhartha S. Srinivasa
Near Optimal Bayesian Active Learning for Decision Making. CoRR (2014)
Yuxin Chen, Hariprasad Sampathkumar, Bo Luo, Xue-wen Chen
iLike: Bridging the Semantic Gap in Vertical Image Search by Integrating Text and Visual Features. IEEE Trans. Knowl. Data Eng. 25 (10) (2013)
Yuxin Chen, Andreas Krause
Near-optimal Batch Mode Active Learning and Adaptive Submodular Optimization. ICML (1) (2013)
Yuxin Chen, Bo Luo
S2A: secure smart household appliances. CODASPY (2012)
Yuanliang Meng, Junyan Li, Patrick Denton, Yuxin Chen, Bo Luo, Paul Selden, Xue-wen Chen
IPKB: a digital library for invertebrate paleontology. JCDL (2012)
Yuxin Chen, Brian Potetz, Bo Luo, Xue-wen Chen, Yunfeng Lin
Cephalometric Landmark Tracing Using Deformable Templates. HISB (2011)
Fengjun Li, Yuxin Chen, Bo Luo, Dongwon Lee, Peng Liu
Privacy Preserving Group Linkage. SSDBM (2011)
Yuxin Chen, Nenghai Yu, Bo Luo, Xue-wen Chen
iLike: integrating visual and textual features for vertical search. ACM Multimedia (2010)