iLike: integrating visual and textual features for vertical search. - Yuxin Chen 001; Nenghai Yu; Bo Luo; Xue-wen Chen 001 (ACM Multimedia, 2010)

Cephalometric Landmark Tracing Using Deformable Templates. - Yuxin Chen 001; Brian Potetz; Bo Luo; Xue-wen Chen 001; Yunfeng Lin (HISB, 2011)

Privacy Preserving Group Linkage. - Fengjun Li; Yuxin Chen 001; Bo Luo; Dongwon Lee 001; Peng Liu 005 (SSDBM, 2011)

S2A: secure smart household appliances. - Yuxin Chen 001; Bo Luo (CODASPY, 2012)

IPKB: a digital library for invertebrate paleontology. - Yuanliang Meng; Junyan Li; Patrick Denton; Yuxin Chen 001; Bo Luo; Paul Selden; Xue-wen Chen 001 (JCDL, 2012)

Near-optimal Batch Mode Active Learning and Adaptive Submodular Optimization. - Yuxin Chen 001; Andreas Krause 001 (ICML (1), 2013)

iLike: Bridging the Semantic Gap in Vertical Image Search by Integrating Text and Visual Features. - Yuxin Chen 001; Hariprasad Sampathkumar; Bo Luo; Xue-wen Chen 001 (IEEE Trans. Knowl. Data Eng., 2013)

Near Optimal Bayesian Active Learning for Decision Making. - Shervin Javdani; Yuxin Chen 001; Amin Karbasi; Andreas Krause 001; Drew Bagnell; Siddhartha S. Srinivasa (AISTATS, 2014)

Active Detection via Adaptive Submodularity. - Yuxin Chen 001; Hiroaki Shioi; Cesar Fuentes Montesinos; Lian Pin Koh; Serge A. Wich; Andreas Krause 001 (ICML, 2014)

Submodular Surrogates for Value of Information. - Yuxin Chen 001; Shervin Javdani; Amin Karbasi; J. Andrew Bagnell; Siddhartha S. Srinivasa; Andreas Krause 001 (AAAI, 2015)

Sequential Information Maximization: When is Greedy Near-optimal? - Yuxin Chen 001; S. Hamed Hassani; Amin Karbasi; Andreas Krause 001 (COLT, 2015)

Near-optimal Bayesian Active Learning with Correlated and Noisy Tests. - Yuxin Chen 001; Seyed Hamed Hassani; Andreas Krause 001 (AISTATS, 2017)

Learning Shape Analysis. - Marc Brockschmidt; Yuxin Chen 001; Pushmeet Kohli; Siddharth Krishna 001; Daniel Tarlow (SAS, 2017)

Efficient Online Learning for Optimizing Value of Information: Theory and Application to Interactive Troubleshooting. - Yuxin Chen 001; Jean-Michel Renders; Morteza Haghir Chehreghani; Andreas Krause 001 (UAI, 2017)

Near-optimal Adaptive Information Acquisition: Theory and Applications. - Yuxin Chen 001 (2017)

Near-Optimal Machine Teaching via Explanatory Teaching Sets. - Yuxin Chen 001; Oisin Mac Aodha; Shihan Su; Pietro Perona; Yisong Yue (AISTATS, 2018)

Teaching Categories to Human Learners With Visual Explanations. - Oisin Mac Aodha; Shihan Su; Yuxin Chen 001; Pietro Perona; Yisong Yue (CVPR, 2018)

Understanding the Role of Adaptivity in Machine Teaching: The Case of Version Space Learners. - Yuxin Chen 001; Adish Singla; Oisin Mac Aodha; Pietro Perona; Yisong Yue (NeurIPS, 2018)

Teaching Multiple Concepts to Forgetful Learners. - Anette Hunziker; Yuxin Chen 001; Oisin Mac Aodha; Manuel Gomez-Rodriguez; Andreas Krause 001; Pietro Perona; Yisong Yue; Adish Singla (CoRR, 2018)

Seeding Deep Learning using Wireless Localization. - Zhujun Xiao; Yanzi Zhu; Yuxin Chen 001; Ben Y. Zhao; Junchen Jiang; Haitao Zheng 001 (CoRR, 2018)

Adversarial WiFi Sensing. - Yanzi Zhu; Zhujun Xiao; Yuxin Chen 001; Zhijing Li 001; Max Liu; Ben Y. Zhao; Haitao Zheng 001 (CoRR, 2018)

Optimizing Photonic Nanostructures via Multi-fidelity Gaussian Processes. - Jialin Song; Yury S. Tokpanov; Yuxin Chen 001; Dagny Fleischman; Kate T. Fountaine; Harry A. Atwater; Yisong Yue (CoRR, 2018)

A General Framework for Multi-fidelity Bayesian Optimization with Gaussian Processes. - Jialin Song; Yuxin Chen 001; Yisong Yue (AISTATS, 2019)

Batched Stochastic Bayesian Optimization via Combinatorial Constraints Design. - Kevin K. Yang; Yuxin Chen 001; Alycia Lee; Yisong Yue (AISTATS, 2019)

Barrier Certificates for Assured Machine Teaching. - Mohamadreza Ahmadi; Bo Wu 005; Yuxin Chen 001; Yisong Yue; Ufuk Topcu (ACC, 2019)

An Encoder-Decoder Based Approach for Anomaly Detection with Application in Additive Manufacturing. - Yingshui Tan; Baihong Jin; Alexander J. Nettekoven; Yuxin Chen 001; Yisong Yue; Ufuk Topcu; Alberto L. Sangiovanni-Vincentelli (ICMLA, 2019)

A One-Class Support Vector Machine Calibration Method for Time Series Change Point Detection. - Baihong Jin; Yuxin Chen 001; Dan Li 016; Kameshwar Poolla; Alberto L. Sangiovanni-Vincentelli (ICPHM, 2019)

Landmark Ordinal Embedding. - Nikhil Ghosh; Yuxin Chen 001; Yisong Yue (NeurIPS, 2019)

Teaching Multiple Concepts to a Forgetful Learner. - Anette Hunziker; Yuxin Chen 001; Oisin Mac Aodha; Manuel Gomez Rodriguez; Andreas Krause 001; Pietro Perona; Yisong Yue; Adish Singla (NeurIPS, 2019)

Preference-Based Batch and Sequential Teaching: Towards a Unified View of Models. - Farnam Mansouri; Yuxin Chen 001; Ara Vartanian; Xiaojin (Jerry) Zhu; Adish Singla (NeurIPS, 2019)

Understanding the Effectiveness of Ultrasonic Microphone Jammer. - Yuxin Chen 001; Huiying Li 001; Steven Nagels; Zhijing Li 001; Pedro Lopes 001; Ben Y. Zhao; Haitao Zheng 001 (CoRR, 2019)

Augmenting Monte Carlo Dropout Classification Models with Unsupervised Learning Tasks for Detecting and Diagnosing Out-of-Distribution Faults. - Baihong Jin; Yingshui Tan; Yuxin Chen 001; Alberto L. Sangiovanni-Vincentelli (CoRR, 2019)

Wearable Microphone Jamming. - Yuxin Chen 001; Huiying Li 001; Shan-Yuan Teng; Steven Nagels; Zhijing Li 001; Pedro Lopes 001; Ben Y. Zhao; Haitao Zheng 001 (CHI, 2020)

Demonstrating Wearable Microphone Jamming. - Yuxin Chen 001; Huiying Li 001; Shan-Yuan Teng; Steven Nagels; Zhijing Li 001; Pedro Lopes 001; Haitao Zheng 001; Ben Y. Zhao (CHI Extended Abstracts, 2020)

An Online Learning Framework for Energy-Efficient Navigation of Electric Vehicles. - Niklas Åkerblom; Yuxin Chen 001; Morteza Haghir Chehreghani (IJCAI, 2020)

Understanding the Power and Limitations of Teaching with Imperfect Knowledge. - Rati Devidze; Farnam Mansouri; Luis Haug; Yuxin Chen 001; Adish Singla (IJCAI, 2020)

Et Tu Alexa? When Commodity WiFi Devices Turn into Adversarial Motion Sensors. - Yanzi Zhu; Zhujun Xiao; Yuxin Chen 001; Zhijing Li 001; Max Liu; Ben Y. Zhao; Heather Zheng (NDSS, 2020)

Adaptive Teaching of Temporal Logic Formulas to Learners with Preferences. - Zhe Xu 005; Yuxin Chen 001; Ufuk Topcu (CoRR, 2020)

Average-case Complexity of Teaching Convex Polytopes via Halfspace Queries. - Akash Kumar 006; Adish Singla; Yisong Yue; Yuxin Chen 001 (CoRR, 2020)

Are Ensemble Classifiers Powerful Enough for the Detection and Diagnosis of Intermediate-Severity Faults? - Baihong Jin; Yingshui Tan; Yuxin Chen 001; Kameshwar Poolla; Alberto L. Sangiovanni-Vincentelli (CoRR, 2020)

Exploiting Uncertainties from Ensemble Learners to Improve Decision-Making in Healthcare AI. - Yingshui Tan; Baihong Jin; Xiangyu Yue 001; Yuxin Chen 001; Alberto L. Sangiovanni-Vincentelli (CoRR, 2020)

Using Ensemble Classifiers to Detect Incipient Anomalies. - Baihong Jin; Yingshui Tan; Albert Liu; Xiangyu Yue 001; Yuxin Chen 001; Alberto L. Sangiovanni-Vincentelli (CoRR, 2020)

Preference-Based Batch and Sequential Teaching. - Farnam Mansouri; Yuxin Chen 001; Ara Vartanian; Xiaojin Zhu 001; Adish Singla (CoRR, 2020)

Adaptive Teaching of Temporal Logic Formulas to Preference-based Learners. - Zhe Xu 005; Yuxin Chen 001; Ufuk Topcu (AAAI, 2021)

The Teaching Dimension of Kernel Perceptron. - Akash Kumar 006; Hanqi Zhang; Adish Singla; Yuxin Chen 001 (AISTATS, 2021)

Demonstrating User Authentication via Electrical Muscle Stimulation. - Yuxin Chen 001; Zhuolin Yang; Ruben Abbou; Pedro Lopes 001; Ben Y. Zhao; Haitao Zheng 001 (CHI Extended Abstracts, 2021)

User Authentication via Electrical Muscle Stimulation. - Yuxin Chen 001; Zhuolin Yang; Ruben Abbou; Pedro Lopes 001; Ben Y. Zhao; Haitao Zheng 001 (CHI, 2021)

Learning to Make Decisions via Submodular Regularization. - Ayya Alieva; Aiden Aceves; Jialin Song; Stephen Mayo; Yisong Yue; Yuxin Chen 001 (ICLR, 2021)

Understanding the Effect of Bias in Deep Anomaly Detection. - Ziyu Ye; Yuxin Chen 001; Haitao Zheng 001 (IJCAI, 2021)

Teaching via Best-Case Counterexamples in the Learning-with-Equivalence-Queries Paradigm. - Akash Kumar 006; Yuxin Chen 001; Adish Singla (NeurIPS, 2021)

Teaching an Active Learner with Contrastive Examples. - Chaoqi Wang; Adish Singla; Yuxin Chen 001 (NeurIPS, 2021)

Towards an Interpretable Data-driven Trigger System for High-throughput Physics Facilities. - Chinmaya Mahesh; Kristin Dona; David W. Miller; Yuxin Chen 001 (CoRR, 2021)

Class-wise Thresholding for Detecting Out-of-Distribution Data. - Matteo Guarrera; Baihong Jin; Tung-Wei Lin; Maria A. Zuluaga; Yuxin Chen 001; Alberto L. Sangiovanni-Vincentelli (CoRR, 2021)

BALanCe: Deep Bayesian Active Learning via Equivalence Class Annealing. - Renyu Zhang; Aly A. Khan; Robert L. Grossman; Yuxin Chen 001 (CoRR, 2021)

Class-wise Thresholding for Robust Out-of-Distribution Detection. - Matteo Guarrera; Baihong Jin; Tung-Wei Lin; Maria A. Zuluaga; Yuxin Chen 001; Alberto L. Sangiovanni-Vincentelli (CVPR Workshops, 2022)

Optimizing Decision Making via Submodular Surrogates. - Yuxin Chen 001 (ISAIM, 2022)

Trip Prediction by Leveraging Trip Histories from Neighboring Users. - Yuxin Chen 001; Morteza Haghir Chehreghani (ITSC, 2022)

Explaining Why: How Instructions and User Interfaces Impact Annotator Rationales When Labeling Text Data. - Jamar L. Sullivan Jr.; William Brackenbury; Andrew McNut; Kevin Bryson 002; Kwam Byll; Yuxin Chen 001; Michael L. Littman; Chenhao Tan; Blase Ur (NAACL-HLT, 2022)

Rethinking Explainability as a Dialogue: A Practitioner's Perspective. - Himabindu Lakkaraju; Dylan Slack; Yuxin Chen 001; Chenhao Tan; Sameer Singh 001 (CoRR, 2022)

Learning Representation for Bayesian Optimization with Collision-free Regularization. - Fengxue Zhang; Brian Nord; Yuxin Chen 001 (CoRR, 2022)

Cost-Effective Online Contextual Model Selection. - Xuefeng Liu; Fangfang Xia; Rick L. Stevens; Yuxin Chen 001 (CoRR, 2022)

Learning Human-Compatible Representations for Case-Based Decision Support. - Han Liu; Yizhou Tian; Chacha Chen; Shi Feng 005; Yuxin Chen 001; Chenhao Tan (ICLR, 2023)

Scalable Batch-Mode Deep Bayesian Active Learning via Equivalence Class Annealing. - Renyu Zhang; Aly A. Khan; Robert L. Grossman; Yuxin Chen 001 (ICLR, 2023)

Active Policy Improvement from Multiple Black-box Oracles. - Xuefeng Liu; Takuma Yoneda; Chaoqi Wang; Matthew R. Walter; Yuxin Chen 001 (ICML, 2023)

Learning Regions of Interest for Bayesian Optimization with Adaptive Level-Set Estimation. - Fengxue Zhang; Jialin Song; James C. Bowden; Alexander Ladd; Yisong Yue; Thomas Desautels; Yuxin Chen 001 (ICML, 2023)

Efficient Online Decision Tree Learning with Active Feature Acquisition. - Arman Rahbar; Ziyu Ye; Yuxin Chen 001; Morteza Haghir Chehreghani (IJCAI, 2023)

Towards a General Video-based Keystroke Inference Attack. - Zhuolin Yang; Yuxin Chen 001; Zain Sarwar; Hadleigh Schwartz; Ben Y. Zhao; Haitao Zheng 001 (USENIX Security Symposium, 2023)

Constrained Bayesian Optimization with Adaptive Active Learning of Unknown Constraints. - Fengxue Zhang; Zejie Zhu; Yuxin Chen 001 (CoRR, 2023)

Online learning of energy consumption for navigation of electric vehicles. - Niklas Åkerblom; Yuxin Chen 001; Morteza Haghir Chehreghani (Artif. Intell., 2023)

Model-based Policy Optimization under Approximate Bayesian Inference. - Chaoqi Wang; Yuxin Chen 001; Kevin Murphy (AISTATS, 2024)

Don't Be Pessimistic Too Early: Look K Steps Ahead! - Chaoqi Wang; Ziyu Ye; Kevin Murphy; Yuxin Chen 001 (AISTATS, 2024)

Blending Imitation and Reinforcement Learning for Robust Policy Improvement. - Xuefeng Liu; Takuma Yoneda; Rick Stevens; Matthew R. Walter; Yuxin Chen 001 (ICLR, 2024)

Beyond Reverse KL: Generalizing Direct Preference Optimization with Diverse Divergence Constraints. - Chaoqi Wang; Yibo Jiang; Chenghao Yang 001; Han Liu; Yuxin Chen 001 (ICLR, 2024)

Enhancing Instance-Level Image Classification with Set-Level Labels. - Renyu Zhang; Aly A. Khan; Yuxin Chen 001; Robert L. Grossman (ICLR, 2024)

Wukong: Towards a Scaling Law for Large-Scale Recommendation. - Buyun Zhang; Liang Luo; Yuxin Chen 001; Jade Nie; Xi Liu; Shen Li; Yanli Zhao; Yuchen Hao; Yantao Yao; Ellie Dingqiao Wen; Jongsoo Park; Maxim Naumov; et al. (ICML, 2024)

Disaggregated Multi-Tower: Topology-aware Modeling Technique for Efficient Large Scale Recommendation. - Liang Luo; Buyun Zhang; Michael Tsang; Yinbin Ma; Ching-Hsiang Chu; Yuxin Chen 001; Shen Li; Yuchen Hao; Yanli Zhao; Guna Lakshminarayanan; Ellie Wen; Jongsoo Park; et al. (MLSys, 2024)

Contextual Active Model Selection. - Xuefeng Liu; Fangfang Xia; Rick Stevens; Yuxin Chen 001 (NeurIPS, 2024)

No-Regret Learning of Nash Equilibrium for Black-Box Games via Gaussian Processes. - Minbiao Han; Fengxue Zhang; Yuxin Chen 001 (UAI, 2024)

Rankitect: Ranking Architecture Search Battling World-class Engineers at Meta Scale. - Wei Wen; Kuang-Hung Liu; Igor Fedorov; Xin Zhang 054; Hang Yin 005; Weiwei Chu; Kaveh Hassani; Mengying Sun; Jiang Liu 011; Xu Wang; Lin Jiang; Yuxin Chen 001; et al. (WWW (Companion Volume), 2024)

AutoML for Large Capacity Modeling of Meta's Ranking Systems. - Hang Yin 005; Kuang-Hung Liu; Mengying Sun; Yuxin Chen 001; Buyun Zhang; Jiang Liu 011; Vivek Sehgal; Rudresh Rajnikant Panchal; Eugen Hotaj; Xi Liu; Daifeng Guo; Jamey Zhang; et al. (WWW (Companion Volume), 2024)

Direct Acquisition Optimization for Low-Budget Active Learning. - Zhuokai Zhao; Yibo Jiang; Yuxin Chen 001 (CoRR, 2024)

Wukong: Towards a Scaling Law for Large-Scale Recommendation. - Buyun Zhang; Liang Luo; Yuxin Chen 001; Jade Nie; Xi Liu; Daifeng Guo; Yanli Zhao; Shen Li; Yuchen Hao; Yantao Yao; Guna Lakshminarayanan; Ellie Dingqiao Wen; et al. (CoRR, 2024)

InterFormer: Towards Effective Heterogeneous Interaction Learning for Click-Through Rate Prediction. - Zhichen Zeng 001; Xiaolong Liu; Mengyue Hang; Xiaoyi Liu; Qinghai Zhou; Chaofei Yang; Yiqun Liu; Yichen Ruan; Laming Chen; Yuxin Chen 001; Yujia Hao; Jiaqi Xu; et al. (CoRR, 2024)

Robust Multi-fidelity Bayesian Optimization with Deep Kernel and Partition. - Fengxue Zhang; Thomas Desautels; Yuxin Chen 001 (AISTATS, 2025)

DrugImproverGPT: A Large Language Model for Drug Optimization with Fine-Tuning via Structured Policy Optimization. - Xuefeng Liu; Songhao Jiang; Siyu Chen; Zhuoran Yang; Yuxin Chen 001; Ian T. Foster; Rick Stevens (CoRR, 2025)

Active Advantage-Aligned Online Reinforcement Learning with Offline Data. - Xuefeng Liu; Hung T. C. Le; Siyu Chen; Rick Stevens; Zhuoran Yang; Matthew R. Walter; Yuxin Chen 001 (CoRR, 2025)

External Large Foundation Model: How to Efficiently Serve Trillions of Parameters for Online Ads Recommendation. - Mingfu Liang; Xi Liu; Rong Jin 001; Boyang Liu; Qiuling Suo; Qinghai Zhou; Song Zhou; Laming Chen; Hua Zheng; Zhiyuan Li; Shali Jiang 003; Jiyan Yang; et al. (CoRR, 2025)

Formal Models of Active Learning from Contrastive Examples. - Farnam Mansouri; Hans Ulrich Simon; Adish Singla; Yuxin Chen 001; Sandra Zilles (CoRR, 2025)