A support vector method for optimizing average precision. - Yisong Yue; Thomas Finley; Filip Radlinski; Thorsten Joachims (SIGIR, 2007)

Predicting diverse subsets using structural SVMs. - Yisong Yue; Thorsten Joachims (ICML, 2008)

Interactively optimizing information retrieval systems as a dueling bandits problem. - Yisong Yue; Thorsten Joachims (ICML, 2009)

Predicting structured objects with support vector machines. - Thorsten Joachims; Thomas Hofmann 001; Yisong Yue; Chun-Nam John Yu (Commun. ACM, 2009)

Multi-Level Structured Models for Document-Level Sentiment Classification. - Ainur Yessenalina; Yisong Yue; Claire Cardie (EMNLP, 2010)

Learning more powerful test statistics for click-based retrieval evaluation. - Yisong Yue; Yue Gao 005; Olivier Chapelle; Ya Zhang 002; Thorsten Joachims (SIGIR, 2010)

Beyond position bias: examining result attractiveness as a source of presentation bias in clickthrough data. - Yisong Yue; Rajan Patel; Hein Roehrig (WWW, 2010)

Beat the Mean Bandit. - Yisong Yue; Thorsten Joachims (ICML, 2011)

Linear Submodular Bandits and their Application to Diversified Retrieval. - Yisong Yue; Carlos Guestrin (NIPS, 2011)

Practical online retrieval evaluation. - Filip Radlinski; Yisong Yue (SIGIR, 2011)

Dynamic ranked retrieval. - Christina Brandt; Thorsten Joachims; Yisong Yue; Jacob Bank (WSDM, 2011)

New Learning Frameworks for Information Retrieval. - Yisong Yue (2011)

An Efficient Simulation-Based Approach to Ambulance Fleet Allocation and Dynamic Redeployment. - Yisong Yue; Lavanya Marla; Ramayya Krishnan (AAAI, 2012)

Hierarchical Exploration for Accelerating Contextual Bandits. - Yisong Yue; Sue Ann Hong; Carlos Guestrin (ICML, 2012)

The K-armed dueling bandits problem. - Yisong Yue; Josef Broder; Robert Kleinberg; Thorsten Joachims (J. Comput. Syst. Sci., 2012)

Large-scale validation and analysis of interleaved search evaluation. - Olivier Chapelle; Thorsten Joachims; Filip Radlinski; Yisong Yue (ACM Trans. Inf. Syst., 2012)

Learning Policies for Contextual Submodular Prediction. - Stéphane Ross; Jiaji Zhou; Yisong Yue; Debadeepta Dey; Drew Bagnell (ICML (3), 2013)

Adaptive collective routing using gaussian process dynamic congestion models. - Siyuan Liu 001; Yisong Yue; Ramayya Krishnan (KDD, 2013)

Knapsack Constrained Contextual Submodular List Prediction with Application to Multi-document Summarization. - Jiaji Zhou; Stéphane Ross; Yisong Yue; Debadeepta Dey; J. Andrew Bagnell (CoRR, 2013)

Large-Scale Analysis of Soccer Matches Using Spatiotemporal Tracking Data. - Alina Bialkowski; Patrick Lucey; Peter Carr 001; Yisong Yue; Sridha Sridharan; Iain A. Matthews (ICDM, 2014)

Identifying Team Style in Soccer Using Formations Learned from Spatiotemporal Tracking Data. - Alina Bialkowski; Patrick Lucey; Peter Carr 001; Yisong Yue; Sridha Sridharan; Iain A. Matthews (ICDM Workshops, 2014)

Learning Fine-Grained Spatial Models for Dynamic Sports Play Prediction. - Yisong Yue; Patrick Lucey; Peter Carr 001; Alina Bialkowski; Iain A. Matthews (ICDM, 2014)

Personalized collaborative clustering. - Yisong Yue; Chong Wang; Khalid El-Arini; Carlos Guestrin (WWW, 2014)

A Decision Tree Framework for Spatiotemporal Sequence Prediction. - Taehwan Kim; Yisong Yue; Sarah L. Taylor; Iain A. Matthews (KDD, 2015)

Smooth Interactive Submodular Set Cover. - Bryan D. He; Yisong Yue (NIPS, 2015)

Non-Myopic Adaptive Route Planning in Uncertain Congestion Environments. - Siyuan Liu 001; Yisong Yue; Ramayya Krishnan (IEEE Trans. Knowl. Data Eng., 2015)

Robust ambulance allocation using risk-based metrics. - Kaushik Krishnan; Lavanya Marla; Yisong Yue (COMSNETS, 2016)

Learning Online Smooth Predictors for Realtime Camera Planning Using Recurrent Decision Trees. - Jianhui Chen; Hoang Minh Le 002; Peter Carr 001; Yisong Yue; James J. Little (CVPR, 2016)

A Rotation Invariant Latent Factor Model for Moveme Discovery from Static Poses. - Matteo Ruggero Ronchi; Joon Sik Kim; Yisong Yue (ICDM, 2016)

Smooth Imitation Learning for Online Sequence Prediction. - Hoang Minh Le 002; Andrew Kang; Yisong Yue; Peter Carr 001 (ICML, 2016)

Chalkboarding: A New Spatiotemporal Query Paradigm for Sports Play Retrieval. - Long Sha; Patrick Lucey; Yisong Yue; Peter Carr 001; Charlie Rohlf; Iain A. Matthews (IUI, 2016)

Generating Long-term Trajectories Using Deep Hierarchical Networks. - Stephan Zheng; Yisong Yue; Jennifer A. Hobbs (NIPS, 2016)

Factorized Variational Autoencoders for Modeling Audience Reactions to Movies. - Zhiwei Deng; Rajitha Navarathna; Peter Carr 001; Stephan Mandt; Yisong Yue; Iain A. Matthews; Greg Mori (CVPR, 2017)

Learning Recurrent Representations for Hierarchical Behavior Modeling. - Eyrun Eyjolfsdottir; Kristin Branson; Yisong Yue; Pietro Perona (ICLR (Poster), 2017)

Coordinated Multi-Agent Imitation Learning. - Hoang Minh Le 002; Yisong Yue; Peter Carr 001; Patrick Lucey (ICML, 2017)

Multi-dueling Bandits with Dependent Arms. - Yanan Sui; Vincent Zhuang; Joel W. Burdick; Yisong Yue (UAI, 2017)

Coordinated Multi-Agent Imitation Learning. - Hoang Minh Le 002; Yisong Yue; Peter Carr 001 (CoRR, 2017)

Correlational Dueling Bandits with Application to Clinical Treatment in Large Decision Spaces. - Yanan Sui; Yisong Yue; Joel W. Burdick (CoRR, 2017)

Generating Long-term Trajectories Using Deep Hierarchical Networks. - Stephan Zheng; Yisong Yue; Patrick Lucey (CoRR, 2017)

Fine-Grained Retrieval of Sports Plays using Tree-Based Alignment of Trajectories. - Long Sha; Patrick Lucey; Stephan Zheng; Taehwan Kim; Yisong Yue; Sridha Sridharan (CoRR, 2017)

Long-term Forecasting using Tensor-Train RNNs. - Rose Yu; Stephan Zheng; Anima Anandkumar; Yisong Yue (CoRR, 2017)

A deep learning approach for generalized speech animation. - Sarah L. Taylor; Taehwan Kim; Yisong Yue; Moshe Mahler; James Krahe; Anastasio Garcia Rodriguez; Jessica K. Hodgins; Iain A. Matthews (ACM Trans. Graph., 2017)

Safe Exploration and Optimization of Constrained MDPs Using Gaussian Processes. - Akifumi Wachi; Yanan Sui; Yisong Yue; Masahiro Ono (AAAI, 2018)

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)

Learning to Infer. - Joseph Marino; Yisong Yue; Stephan Mandt (ICLR (Workshop), 2018)

Hierarchical Imitation and Reinforcement Learning. - Hoang Minh Le 002; Nan Jiang 008; Alekh Agarwal; Miroslav Dudík; Yisong Yue; Hal Daumé III (ICML, 2018)

Iterative Amortized Inference. - Joseph Marino; Yisong Yue; Stephan Mandt (ICML, 2018)

Stagewise Safe Bayesian Optimization with Gaussian Processes. - Yanan Sui; Vincent Zhuang; Joel W. Burdick; Yisong Yue (ICML, 2018)

Advancements in Dueling Bandits. - Yanan Sui; Masrour Zoghi; Katja Hofmann; Yisong Yue (IJCAI, 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)

A General Method for Amortizing Variational Filtering. - Joseph Marino; Milan Cvitkovic; Yisong Yue (NeurIPS, 2018)

Multi-resolution Tensor Learning for Large-Scale Spatial Data. - Stephan Zheng; Rose Yu; Yisong Yue (CoRR, 2018)

Detecting Adversarial Examples via Neural Fingerprinting. - Sumanth Dathathri; Stephan Zheng; Richard M. Murray; Yisong Yue (CoRR, 2018)

Generative Multi-Agent Behavioral Cloning. - Eric Zhan; Stephan Zheng; Yisong Yue; Long Sha; Patrick Lucey (CoRR, 2018)

Learning to Search via Self-Imitation. - Jialin Song; Ravi Lanka; Albert Zhao; Yisong Yue; Masahiro Ono (CoRR, 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)

PhaseLink: A Deep Learning Approach to Seismic Phase Association. - Zachary E. Ross; Yisong Yue; Men-Andrin Meier; Egill Hauksson; Thomas H. Heaton (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)

Interactive Sports Analytics: An Intelligent Interface for Utilizing Trajectories for Interactive Sports Play Retrieval and Analytics. - Long Sha; Patrick Lucey; Yisong Yue; Xinyu Wei; Jennifer A. Hobbs; Charlie Rohlf; Sridha Sridharan (ACM Trans. Comput. Hum. Interact., 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)

A Control Lyapunov Perspective on Episodic Learning via Projection to State Stability. - Andrew J. Taylor; Victor D. Dorobantu; Meera Krishnamoorthy; Hoang Minh Le 002; Yisong Yue; Aaron D. Ames (CDC, 2019)

Generating Multi-Agent Trajectories using Programmatic Weak Supervision. - Eric Zhan; Stephan Zheng; Yisong Yue; Long Sha; Patrick Lucey (ICLR (Poster), 2019)

Batch Policy Learning under Constraints. - Hoang Minh Le 002; Cameron Voloshin; Yisong Yue (ICML, 2019)

Control Regularization for Reduced Variance Reinforcement Learning. - Richard Cheng; Abhinav Verma 001; Gábor Orosz; Swarat Chaudhuri; Yisong Yue; Joel Burdick (ICML, 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)

Neural Lander: Stable Drone Landing Control Using Learned Dynamics. - Guanya Shi; Xichen Shi; Michael O'Connell; Rose Yu; Kamyar Azizzadenesheli; Animashree Anandkumar; Yisong Yue; Soon-Jo Chung (ICRA, 2019)

Episodic Learning with Control Lyapunov Functions for Uncertain Robotic Systems*. - Andrew J. Taylor; Victor D. Dorobantu; Hoang Minh Le 002; Yisong Yue; Aaron D. Ames (IROS, 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)

NAOMI: Non-Autoregressive Multiresolution Sequence Imputation. - Yukai Liu; Rose Yu; Stephan Zheng; Eric Zhan; Yisong Yue (NeurIPS, 2019)

Imitation-Projected Programmatic Reinforcement Learning. - Abhinav Verma 001; Hoang Minh Le 002; Yisong Yue; Swarat Chaudhuri (NeurIPS, 2019)

Co-training for Policy Learning. - Jialin Song; Ravi Lanka; Yisong Yue; Masahiro Ono (UAI, 2019)

Episodic Learning with Control Lyapunov Functions for Uncertain Robotic Systems. - Andrew J. Taylor; Victor D. Dorobantu; Hoang Minh Le 002; Yisong Yue; Aaron D. Ames (CoRR, 2019)

Imitation-Projected Policy Gradient for Programmatic Reinforcement Learning. - Abhinav Verma 001; Hoang Minh Le 002; Yisong Yue; Swarat Chaudhuri (CoRR, 2019)

Dueling Posterior Sampling for Preference-Based Reinforcement Learning. - Ellen R. Novoseller; Yanan Sui; Yisong Yue; Joel W. Burdick (CoRR, 2019)

Triply Robust Off-Policy Evaluation. - Anqi Liu; Hao Liu; Anima Anandkumar; Yisong Yue (CoRR, 2019)

Multiresolution Tensor Learning for Efficient and Interpretable Spatial Analysis. - Jung Yeon Park; Kenneth Theo Carr; Stephan Zheng; Yisong Yue; Rose Yu (ICML, 2020)

Learning Calibratable Policies using Programmatic Style-Consistency. - Eric Zhan; Albert Tseng; Yisong Yue; Adith Swaminathan; Matthew J. Hausknecht (ICML, 2020)

Neural-Swarm: Decentralized Close-Proximity Multirotor Control Using Learned Interactions. - Guanya Shi; Wolfgang Hönig; Yisong Yue; Soon-Jo Chung (ICRA, 2020)

Preference-Based Learning for Exoskeleton Gait Optimization. - Maegan Tucker; Ellen R. Novoseller; Claudia Kann; Yanan Sui; Yisong Yue; Joel W. Burdick; Aaron D. Ames (ICRA, 2020)

Human Preference-Based Learning for High-dimensional Optimization of Exoskeleton Walking Gaits. - Maegan Tucker; Myra Cheng; Ellen R. Novoseller; Richard Cheng; Yisong Yue; Joel W. Burdick; Aaron D. Ames (IROS, 2020)

Robust Regression for Safe Exploration in Control. - Anqi Liu; Guanya Shi; Soon-Jo Chung; Anima Anandkumar; Yisong Yue (L4DC, 2020)

Learning for Safety-Critical Control with Control Barrier Functions. - Andrew J. Taylor; Andrew Singletary; Yisong Yue; Aaron D. Ames (L4DC, 2020)

On the distance between two neural networks and the stability of learning. - Jeremy Bernstein; Arash Vahdat; Yisong Yue; Ming-Yu Liu 001 (NeurIPS, 2020)

Learning compositional functions via multiplicative weight updates. - Jeremy Bernstein; Jiawei Zhao; Markus Meister; Ming-Yu Liu 001; Anima Anandkumar; Yisong Yue (NeurIPS, 2020)

Learning Differentiable Programs with Admissible Neural Heuristics. - Ameesh Shah; Eric Zhan; Jennifer J. Sun; Abhinav Verma 001; Yisong Yue; Swarat Chaudhuri (NeurIPS, 2020)

Online Optimization with Memory and Competitive Control. - Guanya Shi; Yiheng Lin 001; Soon-Jo Chung; Yisong Yue; Adam Wierman (NeurIPS, 2020)

A General Large Neighborhood Search Framework for Solving Integer Linear Programs. - Jialin Song; Ravi Lanka; Yisong Yue; Bistra Dilkina (NeurIPS, 2020)

The Power of Predictions in Online Control. - Chenkai Yu; Guanya Shi; Soon-Jo Chung; Yisong Yue; Adam Wierman (NeurIPS, 2020)

Dueling Posterior Sampling for Preference-Based Reinforcement Learning. - Ellen R. Novoseller; Yibing Wei; Yanan Sui; Yisong Yue; Joel Burdick (UAI, 2020)

Beyond No-Regret: Competitive Control via Online Optimization with Memory. - Guanya Shi; Yiheng Lin 001; Soon-Jo Chung; Yisong Yue; Adam Wierman (CoRR, 2020)

A General Large Neighborhood Search Framework for Solving Integer Programs. - Jialin Song; Ravi Lanka; Yisong Yue; Bistra Dilkina (CoRR, 2020)

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

Graph Neural Networks for the Prediction of Substrate-Specific Organic Reaction Conditions. - Serim Ryou; Michael R. Maser; Alexander Y. Cui; Travis J. DeLano; Yisong Yue; Sarah E. Reisman (CoRR, 2020)

Distributionally Robust Learning for Unsupervised Domain Adaptation. - Haoxuan Wang 002; Anqi Liu; Zhiding Yu; Yisong Yue; Anima Anandkumar (CoRR, 2020)

Architecture Agnostic Neural Networks. - Sabera Talukder; Guruprasad Raghavan; Yisong Yue (CoRR, 2020)

Machine Learning Based Path Planning for Improved Rover Navigation (Pre-Print Version). - Neil Abcouwer; Shreyansh Daftry; Siddarth Venkatraman; Tyler del Sesto; Olivier Toupet; Ravi Lanka; Jialin Song; Yisong Yue; Masahiro Ono (CoRR, 2020)

On the Benefits of Early Fusion in Multimodal Representation Learning. - George Barnum; Sabera Talukder; Yisong Yue (CoRR, 2020)

Task Programming: Learning Data Efficient Behavior Representations. - Jennifer J. Sun; Ann Kennedy; Eric Zhan; Yisong Yue; Pietro Perona (CoRR, 2020)

GLAS: Global-to-Local Safe Autonomy Synthesis for Multi-Robot Motion Planning With End-to-End Learning. - Benjamin Rivière; Wolfgang Hönig; Yisong Yue; Soon-Jo Chung (IEEE Robotics Autom. Lett., 2020)

Deep Bayesian Quadrature Policy Optimization. - Ravi Tej Akella; Kamyar Azizzadenesheli; Mohammad Ghavamzadeh; Animashree Anandkumar; Yisong Yue (AAAI, 2021)

Online Robust Control of Nonlinear Systems with Large Uncertainty. - Dimitar Ho; Hoang Minh Le 001; John Doyle 001; Yisong Yue (AISTATS, 2021)

Minimax Model Learning. - Cameron Voloshin; Nan Jiang 008; Yisong Yue (AISTATS, 2021)

Active Learning under Label Shift. - Eric Zhao 002; Anqi Liu; Animashree Anandkumar; Yisong Yue (AISTATS, 2021)

Towards Robust Data-Driven Control Synthesis for Nonlinear Systems with Actuation Uncertainty. - Andrew J. Taylor; Victor D. Dorobantu; Sarah Dean; Benjamin Recht; Yisong Yue; Aaron D. Ames (CDC, 2021)

Task Programming: Learning Data Efficient Behavior Representations. - Jennifer J. Sun; Ann Kennedy; Eric Zhan; David J. Anderson; Yisong Yue; Pietro Perona (CVPR, 2021)

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

Learning by Turning: Neural Architecture Aware Optimisation. - Yang Liu; Jeremy Bernstein; Markus Meister; Yisong Yue (ICML, 2021)

ROIAL: Region of Interest Active Learning for Characterizing Exoskeleton Gait Preference Landscapes. - Kejun Li; Maegan Tucker; Erdem Biyik; Ellen R. Novoseller; Joel W. Burdick; Yanan Sui; Dorsa Sadigh; Yisong Yue; Aaron D. Ames (ICRA, 2021)

Learning to Control an Unstable System with One Minute of Data: Leveraging Gaussian Process Differentiation in Predictive Control. - Ivan D. Jimenez Rodriguez; Ugo Rosolia; Aaron D. Ames; Yisong Yue (IROS, 2021)

Fine-Grained System Identification of Nonlinear Neural Circuits. - Dawna Bagherian; James Gornet; Jeremy Bernstein; Yu-Li Ni; Yisong Yue; Markus Meister (KDD, 2021)

End-to-End Sequential Sampling and Reconstruction for MRI. - Tianwei Yin; Zihui Wu; He Sun 010; Adrian V. Dalca; Yisong Yue; Katherine L. Bouman (ML4H@NeurIPS, 2021)

DeepGEM: Generalized Expectation-Maximization for Blind Inversion. - Angela F. Gao; Jorge C. Castellanos; Yisong Yue; Zachary E. Ross; Katherine L. Bouman (NeurIPS, 2021)

Iterative Amortized Policy Optimization. - Joseph Marino; Alexandre Piché; Alessandro Davide Ialongo; Yisong Yue (NeurIPS, 2021)

Meta-Adaptive Nonlinear Control: Theory and Algorithms. - Guanya Shi; Kamyar Azizzadenesheli; Michael O'Connell; Soon-Jo Chung; Yisong Yue (NeurIPS, 2021)

The Multi-Agent Behavior Dataset: Mouse Dyadic Social Interactions. - Jennifer J. Sun; Tomomi Karigo; Dipam Chakraborty; Sharada P. Mohanty; Benjamin Wild; Quan Sun; Chen Chen; David J. Anderson; Pietro Perona; Yisong Yue; Ann Kennedy (NeurIPS Datasets and Benchmarks, 2021)

Empirical Study of Off-Policy Policy Evaluation for Reinforcement Learning. - Cameron Voloshin; Hoang Minh Le 002; Nan Jiang 008; Yisong Yue (NeurIPS Datasets and Benchmarks, 2021)

Learning Pseudo-Backdoors for Mixed Integer Programs. - Aaron M. Ferber; Jialin Song; Bistra Dilkina; Yisong Yue (SOCS, 2021)

Competitive policy optimization. - Manish Prajapat; Kamyar Azizzadenesheli; Alexander Liniger; Yisong Yue; Anima Anandkumar (UAI, 2021)

Disentangling Observed Causal Effects from Latent Confounders using Method of Moments. - Anqi Liu; Hao Liu; Tongxin Li; Saeed Karimi-Bidhendi; Yisong Yue; Anima Anandkumar (CoRR, 2021)

Computing the Information Content of Trained Neural Networks. - Jeremy Bernstein; Yisong Yue (CoRR, 2021)

Learning Unstable Dynamics with One Minute of Data: A Differentiation-based Gaussian Process Approach. - Ivan D. Jimenez Rodriguez; Ugo Rosolia; Aaron D. Ames; Yisong Yue (CoRR, 2021)

The Multi-Agent Behavior Dataset: Mouse Dyadic Social Interactions. - Jennifer J. Sun; Tomomi Karigo; Dipam Chakraborty; Sharada P. Mohanty; David J. Anderson; Pietro Perona; Yisong Yue; Ann Kennedy (CoRR, 2021)

End-to-End Sequential Sampling and Reconstruction for MR Imaging. - Tianwei Yin; Zihui Wu; He Sun 010; Adrian V. Dalca; Yisong Yue; Katherine L. Bouman (CoRR, 2021)

Meta-Adaptive Nonlinear Control: Theory and Algorithms. - Guanya Shi; Kamyar Azizzadenesheli; Soon-Jo Chung; Yisong Yue (CoRR, 2021)

Interpreting Expert Annotation Differences in Animal Behavior. - Megan Tjandrasuwita; Jennifer J. Sun; Ann Kennedy; Swarat Chaudhuri; Yisong Yue (CoRR, 2021)

On the Implicit Biases of Architecture & Gradient Descent. - Jeremy Bernstein; Yisong Yue (CoRR, 2021)

A Control Barrier Perspective on Episodic Learning via Projection-to-State Safety. - Andrew J. Taylor; Andrew Singletary; Yisong Yue; Aaron D. Ames (IEEE Control. Syst. Lett., 2021)

Neurosymbolic Programming. - Swarat Chaudhuri; Kevin Ellis; Oleksandr Polozov; Rishabh Singh; Armando Solar-Lezama; Yisong Yue (Found. Trends Program. Lang., 2021)

Multilabel Classification Models for the Prediction of Cross-Coupling Reaction Conditions. - Michael R. Maser; Alexander Y. Cui; Serim Ryou; Travis J. DeLano; Yisong Yue; Sarah E. Reisman (J. Chem. Inf. Model., 2021)

Chance-Constrained Trajectory Optimization for Safe Exploration and Learning of Nonlinear Systems. - Yashwanth Kumar Nakka; Anqi Liu; Guanya Shi; Anima Anandkumar; Yisong Yue; Soon-Jo Chung (IEEE Robotics Autom. Lett., 2021)

Learning Invariant Representation of Tasks for Robust Surgical State Estimation. - Yidan Qin; Max Allan; Yisong Yue; Joel W. Burdick; Mahdi Azizian (IEEE Robotics Autom. Lett., 2021)

Competitive Control with Delayed Imperfect Information. - Chenkai Yu; Guanya Shi; Soon-Jo Chung; Yisong Yue; Adam Wierman (ACC, 2022)

End-to-End Imitation Learning with Safety Guarantees using Control Barrier Functions. - Ryan K. Cosner; Yisong Yue; Aaron D. Ames (CDC, 2022)

Safety of Sampled-Data Systems with Control Barrier Functions via Approximate Discrete Time Models. - Andrew J. Taylor; Victor D. Dorobantu; Ryan K. Cosner; Yisong Yue; Aaron D. Ames (CDC, 2022)

Self-Supervised Keypoint Discovery in Behavioral Videos. - Jennifer J. Sun; Serim Ryou; Roni H. Goldshmid; Brandon Weissbourd; John O. Dabiri; David J. Anderson; Ann Kennedy; Yisong Yue; Pietro Perona (CVPR, 2022)

Automatic Synthesis of Diverse Weak Supervision Sources for Behavior Analysis. - Albert Tseng; Jennifer J. Sun; Yisong Yue (CVPR, 2022)

Investigating Generalization by Controlling Normalized Margin. - Alexander R. Farhang; Jeremy D. Bernstein; Kushal Tirumala; Yang Liu; Yisong Yue (ICML, 2022)

LyaNet: A Lyapunov Framework for Training Neural ODEs. - Ivan Dario Jimenez Rodriguez; Aaron D. Ames; Yisong Yue (ICML, 2022)

Self-Supervised Online Learning for Safety-Critical Control using Stereo Vision. - Ryan K. Cosner; Ivan D. Jimenez Rodriguez; Tamás G. Molnár; Wyatt Ubellacker; Yisong Yue; Aaron D. Ames; Katherine L. Bouman (ICRA, 2022)

Safety-Aware Preference-Based Learning for Safety-Critical Control. - Ryan K. Cosner; Maegan Tucker; Andrew J. Taylor; Kejun Li; Tamás G. Molnár; Wyatt Ubellacker; Anil Alan; Gábor Orosz; Yisong Yue; Aaron D. Ames (L4DC, 2022)

Neural Gaits: Learning Bipedal Locomotion via Control Barrier Functions and Zero Dynamics Policies. - Ivan Dario Jimenez Rodriguez; Noel Csomay-Shanklin; Yisong Yue; Aaron D. Ames (L4DC, 2022)

Policy Optimization with Linear Temporal Logic Constraints. - Cameron Voloshin; Hoang Minh Le 002; Swarat Chaudhuri; Yisong Yue (NeurIPS, 2022)

Deep Neural Imputation: A Framework for Recovering Incomplete Brain Recordings. - Sabera Talukder; Jennifer J. Sun; Matthew Leonard; Bingni W. Brunton; Yisong Yue (CoRR, 2022)

The MABe22 Benchmarks for Representation Learning of Multi-Agent Behavior. - Jennifer J. Sun; Andrew Ulmer; Dipam Chakraborty; Brian Geuther; Edward Hayes; Heng Jia; Vivek Kumar; Zachary Partridge; Alice Robie; Catherine E. Schretter; Chao Sun; Keith Sheppard; et al. (CoRR, 2022)

POLAR: Preference Optimization and Learning Algorithms for Robotics. - Maegan Tucker; Kejun Li; Yisong Yue; Aaron D. Ames (CoRR, 2022)

Neurosymbolic Programming for Science. - Jennifer J. Sun; Megan Tjandrasuwita; Atharva Sehgal; Armando Solar-Lezama; Swarat Chaudhuri; Yisong Yue; Omar Costilla-Reyes (CoRR, 2022)

FI-ODE: Certified and Robust Forward Invariance in Neural ODEs. - Yujia Huang; Ivan Dario Jimenez Rodriguez; Huan Zhang 001; Yuanyuan Shi; Yisong Yue (CoRR, 2022)

BKinD-3D: Self-Supervised 3D Keypoint Discovery from Multi-View Videos. - Jennifer J. Sun; Pierre Karashchuk; Amil Dravid; Serim Ryou; Sonia Fereidooni; John C. Tuthill; Aggelos K. Katsaggelos; Bingni W. Brunton; Georgia Gkioxari; Ann Kennedy; Yisong Yue; Pietro Perona (CoRR, 2022)

Sampled-Data Stabilization With Control Lyapunov Functions via Quadratically Constrained Quadratic Programs. - Andrew J. Taylor; Victor D. Dorobantu; Yisong Yue; Paulo Tabuada; Aaron D. Ames (IEEE Control. Syst. Lett., 2022)

MLNav: Learning to Safely Navigate on Martian Terrains. - Shreyansh Daftry; Neil Abcouwer; Tyler del Sesto; Siddarth Venkatraman; Jialin Song; Lucas Igel; Amos Byon; Ugo Rosolia; Yisong Yue; Masahiro Ono (IEEE Robotics Autom. Lett., 2022)

Natural Multicontact Walking for Robotic Assistive Devices via Musculoskeletal Models and Hybrid Zero Dynamics. - Kejun Li; Maegan Tucker; Rachel Gehlhar; Yisong Yue; Aaron D. Ames (IEEE Robotics Autom. Lett., 2022)

Neural-Fly enables rapid learning for agile flight in strong winds. - Michael O'Connell; Guanya Shi; Xichen Shi; Kamyar Azizzadenesheli; Anima Anandkumar; Yisong Yue; Soon-Jo Chung (Sci. Robotics, 2022)

Unsupervised Learning of Neurosymbolic Encoders. - Eric Zhan; Jennifer J. Sun; Ann Kennedy; Yisong Yue; Swarat Chaudhuri (Trans. Mach. Learn. Res., 2022)

Neural-Swarm2: Planning and Control of Heterogeneous Multirotor Swarms Using Learned Interactions. - Guanya Shi; Wolfgang Hönig; Xichen Shi; Yisong Yue; Soon-Jo Chung (IEEE Trans. Robotics, 2022)

BKinD-3D: Self-Supervised 3D Keypoint Discovery from Multi-View Videos. - Jennifer J. Sun; Lili Karashchuk; Amil Dravid; Serim Ryou; Sonia Fereidooni; John C. Tuthill; Aggelos K. Katsaggelos; Bingni W. Brunton; Georgia Gkioxari; Ann Kennedy; Yisong Yue; Pietro Perona (CVPR, 2023)

MABe22: A Multi-Species Multi-Task Benchmark for Learned Representations of Behavior. - Jennifer J. Sun; Markus Marks; Andrew Wesley Ulmer; Dipam Chakraborty; Brian Geuther; Edward Hayes; Heng Jia; Vivek Kumar; Sebastian Oleszko; Zachary Partridge; Milan Peelman; Alice Robie; et al. (ICML, 2023)

Eventual Discounting Temporal Logic Counterfactual Experience Replay. - Cameron Voloshin; Abhinav Verma 001; Yisong Yue (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)

Learning Calibrated Uncertainties for Domain Shift: A Distributionally Robust Learning Approach. - Haoxuan Wang 002; Zhiding Yu; Yisong Yue; Animashree Anandkumar; Anqi Liu; Junchi Yan (IJCAI, 2023)

Online Adaptive Policy Selection in Time-Varying Systems: No-Regret via Contractive Perturbations. - Yiheng Lin 001; James A. Preiss; Emile Anand; Yingying Li; Yisong Yue; Adam Wierman (NeurIPS, 2023)

SustainGym: Reinforcement Learning Environments for Sustainable Energy Systems. - Christopher Yeh; Victor Li; Rajeev Datta; Julio Arroyo; Nicolas Christianson; Chi Zhang; Yize Chen; Mohammad Mehdi Hosseini; Azarang Golmohammadi; Yuanyuan Shi; Yisong Yue; Adam Wierman (NeurIPS, 2023)

Conformal Generative Modeling on Triangulated Surfaces. - Victor D. Dorobantu; Charlotte Borcherds; Yisong Yue (CoRR, 2023)

Automatic Gradient Descent: Deep Learning without Hyperparameters. - Jeremy Bernstein; Chris Mingard; Kevin Huang; Navid Azizan; Yisong Yue (CoRR, 2023)

Joint-Space Multi-Robot Motion Planning with Learned Decentralized Heuristics. - Fengze Xie; Marcus Dominguez-Kuhne; Benjamin Rivière; Jialin Song; Wolfgang Hönig; Soon-Jo Chung; Yisong Yue (CoRR, 2023)

Compactly Restrictable Metric Policy Optimization Problems. - Victor D. Dorobantu; Kamyar Azizzadenesheli; Yisong Yue (IEEE Trans. Autom. Control., 2023)

The Mixed-Observable Constrained Linear Quadratic Regulator Problem: The Exact Solution and Practical Algorithms. - Ugo Rosolia; Yuxiao Chen 001; Shreyansh Daftry; Masahiro Ono; Yisong Yue; Aaron D. Ames (IEEE Trans. Autom. Control., 2023)

Constructive Nonlinear Control of Underactuated Systems via Zero Dynamics Policies. - William D. Compton; Ivan Dario Jimenez Rodriguez; Noel Csomay-Shanklin; Yisong Yue; Aaron D. Ames (CDC, 2024)

Humanlike Behavior in a Third-Person Shooter with Imitation Learning. - Alexander R. Farhang; Brendan Mulcahy; Daniel Holden; Iain Matthews; Yisong Yue (CoG, 2024)

Online Policy Optimization in Unknown Nonlinear Systems. - Yiheng Lin 001; James A. Preiss; Fengze Xie; Emile Anand; Soon-Jo Chung; Yisong Yue; Adam Wierman (COLT, 2024)

Uncertainty Calibration for Tool-Using Language Agents. - Hao Liu; Zi-Yi Dou; Yixin Wang; Nanyun Peng 001; Yisong Yue (EMNLP (Findings), 2024)

SceneCraft: An LLM Agent for Synthesizing 3D Scenes as Blender Code. - Ziniu Hu; Ahmet Iscen; Aashi Jain; Thomas Kipf; Yisong Yue; David A. Ross; Cordelia Schmid; Alireza Fathi (ICML, 2024)

Symbolic Music Generation with Non-Differentiable Rule Guided Diffusion. - Yujia Huang; Adishree Ghatare; Yuanzhe Liu 001; Ziniu Hu; Qinsheng Zhang; Chandramouli Shama Sastry; Siddharth Gururani; Sageev Oore; Yisong Yue (ICML, 2024)

Feature Reuse and Scaling: Understanding Transfer Learning with Protein Language Models. - Francesca-Zhoufan Li; Ava P. Amini; Yisong Yue; Kevin K. Yang; Alex Xijie Lu (ICML, 2024)

Hierarchical Meta-learning-based Adaptive Controller. - Fengze Xie; Guanya Shi; Michael O'Connell; Yisong Yue; Soon-Jo Chung (ICRA, 2024)

Robust Agility via Learned Zero Dynamics Policies. - Noel Csomay-Shanklin; William D. Compton; Ivan Dario Jimenez Rodriguez; Eric R. Ambrose; Yisong Yue; Aaron D. Ames (IROS, 2024)

Data-Driven Predictive Control for Robust Exoskeleton Locomotion. - Kejun Li; Jeeseop Kim; Xiaobin Xiong; Kaveh Akbari Hamed; Yisong Yue; Aaron D. Ames (IROS, 2024)

Practical Bayesian Algorithm Execution via Posterior Sampling. - Chu Xin Cheng; Raul Astudillo; Thomas A. Desautels; Yisong Yue (NeurIPS, 2024)

Disentangling Linear Quadratic Control with Untrusted ML Predictions. - Tongxin Li; Hao Liu; Yisong Yue (NeurIPS, 2024)

Principled Probabilistic Imaging using Diffusion Models as Plug-and-Play Priors. - Zihui Wu; Yu Sun 022; Yifan Chen; Bingliang Zhang; Yisong Yue; Katherine L. Bouman (NeurIPS, 2024)

CARE: a Benchmark Suite for the Classification and Retrieval of Enzymes. - Jason Yang; Ariane Mora; Shengchao Liu; Bruce J. Wittmann; Animashree Anandkumar; Frances H. Arnold; Yisong Yue (NeurIPS, 2024)

SciInstruct: a Self-Reflective Instruction Annotated Dataset for Training Scientific Language Models. - Dan Zhang; Ziniu Hu; Sining Zhoubian; Zhengxiao Du; Kaiyu Yang; Zihan Wang; Yisong Yue; Yuxiao Dong; Jie Tang 001 (NeurIPS, 2024)

ReST-MCTS*: LLM Self-Training via Process Reward Guided Tree Search. - Dan Zhang; Sining Zhoubian; Ziniu Hu; Yisong Yue; Yuxiao Dong; Jie Tang 001 (NeurIPS, 2024)

Distributionally Robust Constrained Reinforcement Learning under Strong Duality. - Zhengfei Zhang; Kishan Panaganti; Laixi Shi; Yanan Sui; Adam Wierman; Yisong Yue (RLJ, 2024)

SciGLM: Training Scientific Language Models with Self-Reflective Instruction Annotation and Tuning. - Dan Zhang; Ziniu Hu; Sining Zhoubian; Zhengxiao Du; Kaiyu Yang; Zihan Wang; Yisong Yue; Yuxiao Dong; Jie Tang 001 (CoRR, 2024)

Generalizability Under Sensor Failure: Tokenization + Transformers Enable More Robust Latent Spaces. - Geeling Chau; Yujin An; Ahamed Raffey Iqbal; Soon-Jo Chung; Yisong Yue; Sabera Talukder (CoRR, 2024)

SceneCraft: An LLM Agent for Synthesizing 3D Scene as Blender Code. - Ziniu Hu; Ahmet Iscen; Aashi Jain; Thomas Kipf; Yisong Yue; David A. Ross; Cordelia Schmid; Alireza Fathi (CoRR, 2024)

Self-Control of LLM Behaviors by Compressing Suffix Gradient into Prefix Controller. - Min Cai; Yuchen Zhang; Shichang Zhang; Fan Yin; Difan Zou; Yisong Yue; Ziniu Hu (CoRR, 2024)

Population Transformer: Learning Population-level Representations of Intracranial Activity. - Geeling Chau; Christopher Wang; Sabera Talukder; Vighnesh Subramaniam; Saraswati Soedarmadji; Yisong Yue; Boris Katz; Andrei Barbu (CoRR, 2024)

ReST-MCTS*: LLM Self-Training via Process Reward Guided Tree Search. - Dan Zhang; Sining Zhoubian; Yisong Yue; Yuxiao Dong; Jie Tang 001 (CoRR, 2024)

Beyond Numeric Awards: In-Context Dueling Bandits with LLM Agents. - Fanzeng Xia; Hao Liu; Yisong Yue; Tongxin Li (CoRR, 2024)

Strategist: Learning Strategic Skills by LLMs via Bi-Level Tree Search. - Jonathan Light; Min Cai; Weiqin Chen 003; Guanzhi Wang; Xiusi Chen; Wei Cheng; Yisong Yue; Ziniu Hu (CoRR, 2024)

End-to-End Conformal Calibration for Optimization Under Uncertainty. - Christopher Yeh; Nicolas Christianson; Alan Wu; Adam Wierman; Yisong Yue (CoRR, 2024)

Unsupervised Representation Learning from Sparse Transformation Analysis. - Yue Song; T. Anderson Keller 001; Yisong Yue; Pietro Perona; Max Welling (CoRR, 2024)

Find Any Part in 3D. - Ziqi Ma; Yisong Yue; Georgia Gkioxari (CoRR, 2024)

PIANIST: Learning Partially Observable World Models with LLMs for Multi-Agent Decision Making. - Jonathan Light; Sixue Xing; Yuanzhe Liu 001; Weiqin Chen 003; Min Cai; Xiusi Chen; Guanzhi Wang; Wei Cheng; Yisong Yue; Ziniu Hu (CoRR, 2024)

Distributionally Robust Policy Evaluation under General Covariate Shift in Contextual Bandits. - Yihong Guo; Hao Liu; Yisong Yue; Anqi Liu (Trans. Mach. Learn. Res., 2024)

TOTEM: TOkenized Time Series EMbeddings for General Time Series Analysis. - Sabera J. Talukder; Yisong Yue; Georgia Gkioxari (Trans. Mach. Learn. Res., 2024)

Beyond Numeric Rewards: In-Context Dueling Bandits with LLM Agents. - Fanzeng Xia; Hao Liu; Yisong Yue; Tongxin Li (ACL (Findings), 2025)

Visual Agentic AI for Spatial Reasoning with a Dynamic API. - Damiano Marsili; Rohun Agrawal; Yisong Yue; Georgia Gkioxari (CVPR, 2025)

Self-Evolving Visual Concept Library using Vision-Language Critics. - Atharva Sehgal; Patrick Yuan; Ziniu Hu; Yisong Yue; Jennifer J. Sun; Swarat Chaudhuri (CVPR, 2025)

Population Transformer: Learning Population-level Representations of Neural Activity. - Geeling Chau; Christopher Wang; Sabera J. Talukder; Vighnesh Subramaniam; Saraswati Soedarmadji; Yisong Yue; Boris Katz; Andrei Barbu (ICLR, 2025)

Strategist: Self-improvement of LLM Decision Making via Bi-Level Tree Search. - Jonathan Light; Min Cai; Weiqin Chen 003; Guanzhi Wang; Xiusi Chen; Wei Cheng; Yisong Yue; Ziniu Hu (ICLR, 2025)

InverseBench: Benchmarking Plug-and-Play Diffusion Priors for Inverse Problems in Physical Sciences. - Hongkai Zheng; Wenda Chu; Bingliang Zhang; Zihui Wu; Austin Wang; Berthy Feng; Caifeng Zou; Yu Sun 022; Nikola Borislavov Kovachki; Zachary E. Ross; Katherine L. Bouman; Yisong Yue (ICLR, 2025)

Morphological-Symmetry-Equivariant Heterogeneous Graph Neural Network for Robotic Dynamics Learning. - Fengze Xie; Sizhe Wei; Yue Song; Yisong Yue; Lu Gan (L4DC, 2025)

Preferential Multi-Objective Bayesian Optimization. - Raul Astudillo; Kejun Li; Maegan Tucker; Chu Xin Cheng; Aaron D. Ames; Yisong Yue (Trans. Mach. Learn. Res., 2025)

Ensemble Kalman Diffusion Guidance: A Derivative-free Method for Inverse Problems. - Hongkai Zheng; Wenda Chu; Austin Wang; Nikola Borislavov Kovachki; Ricardo Baptista; Yisong Yue (Trans. Mach. Learn. Res., 2025)

DataSciBench: An LLM Agent Benchmark for Data Science. - Dan Zhang; Sining Zhoubian; Min Cai; Fengzu Li; Lekang Yang; Wei Wang 074; Tianjiao Dong; Ziniu Hu; Jie Tang 001; Yisong Yue (CoRR, 2025)

Split Gibbs Discrete Diffusion Posterior Sampling. - Wenda Chu; Yang Song; Yisong Yue (CoRR, 2025)

STeP: A General and Scalable Framework for Solving Video Inverse Problems with Spatiotemporal Diffusion Priors. - Bingliang Zhang; Zihui Wu; Berthy T. Feng; Yang Song; Yisong Yue; Katherine L. Bouman (CoRR, 2025)

CLEVER: A Curated Benchmark for Formally Verified Code Generation. - Amitayush Thakur; Jasper Lee; George Tsoukalas; Meghana Sistla; Matthew Zhao; Stefan Zetzsche; Greg Durrett; Yisong Yue; Swarat Chaudhuri (CoRR, 2025)

Steering Generative Models with Experimental Data for Protein Fitness Optimization. - Jason Yang; Wenda Chu; Daniel Khalil; Raul Astudillo; Bruce J. Wittmann; Frances H. Arnold; Yisong Yue (CoRR, 2025)

Escaping Plato's Cave: JAM for Aligning Independently Trained Vision and Language Models. - Lauren Hyoseo Yoon; Yisong Yue; Been Kim (CoRR, 2025)

Discrete Diffusion Trajectory Alignment via Stepwise Decomposition. - Jiaqi Han; Austin Wang; Minkai Xu; Wenda Chu; Meihua Dang; Yisong Yue; Stefano Ermon (CoRR, 2025)

Fast Non-Episodic Adaptive Tuning of Robot Controllers with Online Policy Optimization. - James A. Preiss; Fengze Xie; Yiheng Lin 001; Adam Wierman; Yisong Yue (CoRR, 2025)

Langevin Flows for Modeling Neural Latent Dynamics. - Yue Song; T. Anderson Keller 001; Yisong Yue; Pietro Perona; Max Welling (CoRR, 2025)

CLF-RL: Control Lyapunov Function Guided Reinforcement Learning. - Kejun Li; Zachary Olkin; Yisong Yue; Aaron D. Ames (CoRR, 2025)

Hybrid Data-Driven Predictive Control for Robust and Reactive Exoskeleton Locomotion Synthesis. - Kejun Li; Jeeseop Kim; Maxime Brunet; Marine Pétriaux; Yisong Yue; Aaron D. Ames (CoRR, 2025)