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Israel, Uriah and Marks, Markus, et el. (2024) A Foundation Model for Cell Segmentation ; bioRvix; 2023.11.17.567630; PMCID PMC10690226; 10.1101/2023.11.17.567630
Yang, Jason and Ducharme, Julie, et el. (2024) Correction to "DeCOIL: Optimization of Degenerate Codon Libraries for Machine Learning-Assisted Protein Engineering" ; ACS Synthetic Biology; Vol. 13; No. 2; 692; 10.1021/acssynbio.3c00751
Talukder, Sabera and Yue, Yisong, et el. (2024) TOTEM: TOkenized Time Series EMbeddings for General Time Series Analysis ; 10.48550/arxiv.2402.16412
Dorobantu, Victor D. and Azizzadenesheli, Kamyar, et el. (2023) Compactly Restrictable Metric Policy Optimization Problems ; IEEE Transactions on Automatic Control; Vol. 68; No. 5; 3115-3122; 10.1109/tac.2022.3217269
Voloshin, Cameron and Verma, Abhinav, et el. (2023) Eventual Discounting Temporal Logic Counterfactual Experience Replay
Sun, Jennifer J. and Tjandrasuwita, Megan, et el. (2022) Neurosymbolic Programming for Science ; 10.48550/arXiv.2210.05050
Huang, Yujia and Jimenez Rodriguez, Ivan Dario, et el. (2022) FI-ODE: Certified and Robust Forward Invariance in Neural ODEs ; 10.48550/arXiv.2210.16940
Tucker, Maegan and Li, Kejun, et el. (2022) POLAR: Preference Optimization and Learning Algorithms for Robotics ; 10.48550/arXiv.2208.04404
Sun, Jennifer J. and Ulmer, Andrew, et el. (2022) The MABe22 Benchmarks for Representation Learning of Multi-Agent Behavior ; 10.48550/arXiv.2207.10553
Sun, Jennifer J. and Karashchuk, Pierre, et el. (2022) BKinD-3D: Self-Supervised 3D Keypoint Discovery from Multi-View Videos ; 10.48550/arXiv.2212.07401
Voloshin, Cameron and Le, Hoang M., et el. (2022) Policy Optimization with Linear Temporal Logic Constraints ; 10.48550/arXiv.arXiv.2206.09546
Talukder, Sabera and Sun, Jennifer J., et el. (2022) Deep Neural Imputation: A Framework for Recovering Incomplete Brain Recordings ; 10.48550/arXiv.arXiv.2206.08094
Dorobantu, Victor D. and Azizzadenesheli, Kamyar, et el. (2022) Compactly Restrictable Metric Policy Optimization Problems ; 10.48550/arXiv.arXiv.2207.05850
Farhang, Alexander R. and Bernstein, Jeremy D., et el. (2022) Investigating Generalization by Controlling Normalized Margin ; Proceedings of Machine Learning Research; Vol. 162; 6324-6336; 10.48550/arXiv.arXiv.2205.03940
O'Connell, Michael and Shi, Guanya, et el. (2022) Neural-Fly enables rapid learning for agile flight in strong winds ; Science Robotics; Vol. 7; No. 66; Art. No. eabm6597; 10.1126/scirobotics.abm6597
Jimenez Rodriguez, Ivan Dario and Csomay-Shanklin, Noel, et el. (2022) Neural Gaits: Learning Bipedal Locomotion via Control Barrier Functions and Zero Dynamics Policies ; Proceedings of Machine Learning Research; Vol. 168; 1060-1072; 10.48550/arXiv.2204.08120
Shi, Guanya and Hönig, Wolfgang, et el. (2022) Neural-Swarm2: Planning and Control of Heterogeneous Multirotor Swarms Using Learned Interactions ; IEEE Transactions on Robotics; Vol. 38; No. 2; 1063-1079; 10.1109/TRO.2021.3098436
Daftry, Shreyansh and Abcouwer, Neil, et el. (2022) MLNav: Learning to Safely Navigate on Martian Terrains ; IEEE Robotics and Automation Letters; Vol. 7; No. 2; 5461-5468; 10.1109/lra.2022.3156654
Li, Kejun and Tucker, Maegan, et el. (2022) Natural Multicontact Walking for Robotic Assistive Devices via Musculoskeletal Models and Hybrid Zero Dynamics ; IEEE Robotics and Automation Letters; Vol. 7; No. 2; 4283-4290; 10.1109/lra.2022.3149568
Taylor, Andrew J. and Dorobantu, Victor D., et el. (2022) Safety of Sampled-Data Systems with Control Barrier Functions via Approximate Discrete Time Models ; 10.48550/arXiv.2203.11470
Cosner, Ryan K. and Jimenez Rodriguez, Ivan D., et el. (2022) Self-Supervised Online Learning for Safety-Critical Control using Stereo Vision ; 10.48550/arXiv.2203.01404
Zhan, Eric and Sun, Jennifer J., et el. (2022) Unsupervised Learning of Neurosymbolic Encoders ; 10.48550/arXiv.2107.13132
Bernstein, Jeremy and Farhang, Alex, et el. (2022) Kernel Interpolation as a Bayes Point Machine ; 10.48550/arXiv.2110.04274
Tseng, Albert and Sun, Jennifer J., et el. (2022) Automatic Synthesis of Diverse Weak Supervision Sources for Behavior Analysis ; 10.48550/arXiv.2111.15186
Cosner, Ryan K. and Tucker, Maegan, et el. (2022) Safety-Aware Preference-Based Learning for Safety-Critical Control ; 10.48550/arXiv.2112.08516
Sun, Jennifer J. and Ryou, Serim, et el. (2022) Self-Supervised Keypoint Discovery in Behavioral Videos ; 10.48550/arXiv.2112.05121
Jimenez Rodriguez, Ivan Dario and Ames, Aaron D., et el. (2022) LyaNet: A Lyapunov Framework for Training Neural ODEs ; 10.48550/arXiv.2202.02526
Tjandrasuwita, Megan and Sun, Jennifer J., et el. (2022) Interpreting Expert Annotation Differences in Animal Behavior ; 10.48550/arXiv.2106.06114
Jimenez Rodriguez, Ivan Dario and Ames, Aaron D., et el. (2022) LyaNet: A Lyapunov Framework for Training Neural ODEs ; Proceedings of Machine Learning Research; 18687-18703; 10.48550/arXiv.arXiv.2202.02526
Taylor, Andrew J. and Dorobantu, Victor D., et el. (2022) Sampled-Data Stabilization with Control Lyapunov Functions via Quadratically Constrained Quadratic Programs ; IEEE Control Systems Letters; Vol. 6; 680-685; 10.1109/LCSYS.2021.3085172
Taylor, Andrew J. and Dorobantu, Victor D., et el. (2021) Towards Robust Data-Driven Control Synthesis for Nonlinear Systems with Actuation Uncertainty ; ISBN 978-1-6654-3659-5; 2021 60th IEEE Conference on Decision and Control (CDC); 6469-6476; 10.1109/CDC45484.2021.9683511
Gao, Angela F. and Castellanos, Jorge C., et el. (2021) DeepGEM: Generalized Expectation-Maximization for Blind Inversion ; ISBN 9781713845393; 35th Conference on Neural Information Processing Systems; 1-12
Shi, Guanya and Azizzadenesheli, Kamyar, et el. (2021) Meta-Adaptive Nonlinear Control: Theory and Algorithms ; 10.48550/arXiv.2106.06098
Wittmann, Bruce J. and Yue, Yisong, et el. (2021) Informed training set design enables efficient machine learning-assisted directed protein evolution ; Cell Systems; Vol. 12; No. 11; 1026-1045; 10.1016/j.cels.2021.07.008
Jimenez Rodriguez, Ivan D. and Rosolia, Ugo, et el. (2021) Learning to Control an Unstable System with One Minute of Data: Leveraging Gaussian Process Differentiation in Predictive Control ; ISBN 978-1-6654-1714-3; 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS); 3896-3903; 10.1109/IROS51168.2021.9636786
Bagherian, Dawna and Gornet, James, et el. (2021) Fine-Grained System Identification of Nonlinear Neural Circuits ; ISBN 978-1-4503-8332-5; Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining; 14-24; 10.1145/3447548.3467402
Ferber, Aaron and Song, Jialin, et el. (2021) Learning Pseudo-Backdoors for Mixed Integer Programs ; 10.48550/arXiv.2106.05080
Taylor, Andrew J. and Singletary, Andrew, et el. (2021) A Control Barrier Perspective on Episodic Learning via Projection-to-State Safety ; IEEE Control Systems Letters; Vol. 5; No. 3; 1019-1024; 10.1109/LCSYS.2020.3009082
Liu, Yang and Bernstein, Jeremy, et el. (2021) Learning by Turning: Neural Architecture Aware Optimisation ; Proceedings of Machine Learning Research; Vol. 139; 6748-6758; 10.48550/arXiv.2102.07227
Yin, Tianwei and Wu, Zihui, et el. (2021) End-to-End Sequential Sampling and Reconstruction for MR Imaging ; 10.48550/arXiv.2105.06460
Sun, Jennifer J. and Kennedy, Ann, et el. (2021) Task Programming: Learning Data Efficient Behavior Representations ; ISBN 978-1-6654-4509-2; 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR); 2875-2884; 10.1109/CVPR46437.2021.00290
Li, Kejun and Tucker, Maegan, et el. (2021) ROIAL: Region of Interest Active Learning for Characterizing Exoskeleton Gait Preference Landscapes ; ISBN 978-1-7281-9077-8; 2021 IEEE International Conference on Robotics and Automation (ICRA); 3212-3218; 10.1109/ICRA48506.2021.9560840
Ravi Tej, Akella and Azizzadenesheli, Kamyar, et el. (2021) Deep Bayesian Quadrature Policy Optimization ; 10.48550/arXiv.2006.15637
Sun, Jennifer J. and Karigo, Tomomi, et el. (2021) The Multi-Agent Behavior Dataset: Mouse Dyadic Social Interactions ; 10.48550/arXiv.2104.02710
Ho, Dimitar and Le, Hoang M., et el. (2021) Online Robust Control of Nonlinear Systems with Large Uncertainty ; Proceedings of Machine Learning Research; Vol. 130; 3475-3483; 10.48550/arXiv.2103.11055
Nakka, Yashwanth Kumar and Liu, Anqi, et el. (2021) Chance-Constrained Trajectory Optimization for Safe Exploration and Learning of Nonlinear Systems ; IEEE Robotics and Automation Letters; Vol. 6; No. 2; 389-396; 10.1109/LRA.2020.3044033
Zhao, Eric and Liu, Anqi, et el. (2021) Active Learning under Label Shift ; Proceedings of Machine Learning Research; Vol. 130; 3412-3420; 10.48550/arXiv.2007.08479
Voloshin, Cameron and Jiang, Nan, et el. (2021) Minimax Model Learning ; Proceedings of Machine Learning Research; Vol. 130; 1612-1620; 10.48550/arXiv.2103.02084
Qin, Yidan and Allan, Max, et el. (2021) Learning Invariant Representation of Tasks for Robust Surgical State Estimation ; IEEE Robotics and Automation Letters; Vol. 6; No. 2; 3208-3215; 10.1109/LRA.2021.3063014
Bernstein, Jeremy and Yue, Yisong (2021) Computing the Information Content of Trained Neural Networks ; 10.48550/arXiv.2103.01045
Abcouwer, Neil and Daftry, Shreyansh, et el. (2021) Machine Learning Based Path Planning for Improved Rover Navigation ; ISBN 978-1-7281-7436-5; 2021 IEEE Aerospace Conference; 1-9; 10.1109/AERO50100.2021.9438337
Liu, Anqi and Liu, Hao, et el. (2021) Disentangling Observed Causal Effects from Latent Confounders using Method of Moments ; 10.48550/arXiv.2101.06614
Cross, Logan and Cockburn, Jeffrey, et el. (2021) Using deep reinforcement learning to reveal how the brain encodes abstract state-space representations in high-dimensional environments ; Neuron; Vol. 109; No. 4; 724-738; PMCID PMC7897245; 10.1016/j.neuron.2020.11.021
Maser, Michael R. and Cui, Alexander Y., et el. (2021) Multilabel Classification Models for the Prediction of Cross-Coupling Reaction Conditions ; Journal of Chemical Information and Modeling; Vol. 61; No. 1; 156-166; 10.1021/acs.jcim.0c01234
Barnum, George and Talukder, Sabera, et el. (2021) On the Benefits of Early Fusion in Multimodal Representation Learning ; 10.48550/arXiv.2011.07191
Talukder, Sabera and Raghavan, Guruprasad, et el. (2021) Architecture Agnostic Neural Networks ; 10.48550/arXiv.2011.02712
Yu, Chenkai and Shi, Guanya, et el. (2020) The Power of Predictions in Online Control ; ISBN 9781713829546; 34th Conference on Neural Information Processing Systems (NeurIPS 2020); 1-11
Marino, Joseph and Piché, Alexandre, et el. (2020) Iterative Amortized Policy Optimization ; ISBN 9781713829546; 34th Conference on Neural Information Processing Systems (NeurIPS 2020); 1-15
Bernstein, Jeremy and Zhao, Jiawei, et el. (2020) Learning compositional functions via multiplicative weight updates ; 10.48550/arXiv.2006.14560
Shi, Guanya and Lin, Yiheng, et el. (2020) Online Optimization with Memory and Competitive Control ; ISBN 9781713829546; 34th Conference on Neural Information Processing Systems (NeurIPS 2020); 1-12
Bernstein, Jeremy and Vahdat, Arash, et el. (2020) On the distance between two neural networks and the stability of learning ; ISBN 9781713829546; Advances in Neural Information Processing Systems 33 (NeurIPS 2020); 1-12
Song, Jialin and Lanka, Ravi, et el. (2020) A General Large Neighborhood Search Framework for Solving Integer Programs ; ISBN 9781713829546; 34th Conference on Neural Information Processing Systems (NeurIPS 2020); 1-12
Kumar, Akash and Singla, Adish, et el. (2020) Average-case Complexity of Teaching Convex Polytopes via Halfspace Queries ; 10.48550/arXiv.2006.14677
Ryou, Serim and Maser, Michael R., et el. (2020) Graph Neural Networks for the Prediction of Substrate-Specific Organic Reaction Conditions ; 10.48550/arXiv.2007.04275
Yu, Chenkai and Shi, Guanya, et el. (2020) Competitive Control with Delayed Imperfect Information ; 10.48550/arXiv.2010.11637
Shah, Ameesh and Zhan, Eric, et el. (2020) Learning Differentiable Programs with Admissible Neural Heuristics ; 10.48550/arXiv.2007.12101
Marino, Joseph and Piché, Alexandre, et el. (2020) Iterative Amortized Policy Optimization ; 10.48550/arXiv.2010.10670
Wang, Haoxuan and Liu, Anqi, et el. (2020) Distributionally Robust Learning for Unsupervised Domain Adaptation ; 10.48550/arXiv.2010.05784
Prajapat, Manish and Azizzadenesheli, Kamyar, et el. (2020) Competitive Policy Optimization ; 10.48550/arXiv.2006.10611
Tucker, Maegan and Cheng, Myra, et el. (2020) Human Preference-Based Learning for High-dimensional Optimization of Exoskeleton Walking Gaits ; ISBN 978-1-7281-6212-6; 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS); 3423-3430; 10.1109/IROS45743.2020.9341416
Novoseller, Ellen R. and Wei, Yibing, et el. (2020) Dueling Posterior Sampling for Preference-Based Reinforcement Learning ; Proceedings of Machine Learning Research; Vol. 124; 1029-1038; 10.48550/arXiv.1908.01289
Shi, Guanya and Hönig, Wolfgang, et el. (2020) Neural-Swarm: Decentralized Close-Proximity Multirotor Control Using Learned Interactions ; ISBN 978-1-7281-7395-5; 2020 IEEE International Conference on Robotics and Automation (ICRA); 3241-3247; 10.1109/ICRA40945.2020.9196800
Tucker, Maegan and Novoseller, Ellen, et el. (2020) Preference-Based Learning for Exoskeleton Gait Optimization ; ISBN 978-1-7281-7395-5; 2020 IEEE International Conference on Robotics and Automation (ICRA); 2351-2357; 10.1109/ICRA40945.2020.9196661
Yu, Chenkai and Shi, Guanya, et el. (2020) The Power of Predictions in Online Control ; 10.48550/arXiv.2006.07569
Rivière, Benjamin and Hönig, Wolfgang, et el. (2020) GLAS: Global-to-Local Safe Autonomy Synthesis for Multi-Robot Motion Planning with End-to-End Learning ; IEEE Robotics and Automation Letters; Vol. 5; No. 3; 4249-4256; 10.1109/lra.2020.2994035
Taylor, Andrew J. and Singletary, Andrew, et el. (2020) Learning for Safety-Critical Control with Control Barrier Functions ; Proceedings of Machine Learning Research; Vol. 120; 708-717; 10.48550/arXiv.1912.10099
Song, Jialin and Lanka, Ravi, et el. (2020) A General Large Neighborhood Search Framework for Solving Integer Programs ; 10.48550/arXiv.2004.00422
Song, Jialin and Tokpanov, Yury S., et el. (2020) Mirrored Plasmonic Filter Design via Active Learning of Multi-Fidelity Physical Models ; ISBN 9781943580767; 2020 Conference on Lasers and Electro-Optics (CLEO); Art. No. JTu2D.6; 10.1364/cleo_at.2020.jtu2d.6
Shi, Guanya and Lin, Yiheng, et el. (2020) Online Optimization with Memory and Competitive Control ; 10.48550/arXiv.2002.05318
Park, Jung Yeon and Carr, Kenneth Theo, et el. (2020) Multiresolution Tensor Learning for Efficient and Interpretable Spatial Analysis ; 10.48550/arXiv.2002.05578
Bernstein, Jeremy and Vahdat, Arash, et el. (2020) On the distance between two neural networks and the stability of learning ; 10.48550/arXiv.2002.03432
Liu, Anqi and Liu, Hao, et el. (2020) Triply Robust Off-Policy Evaluation ; 10.48550/arXiv.1911.05811
Voloshin, Cameron and Le, Hoang M., et el. (2020) Empirical Study of Off-Policy Policy Evaluation for Reinforcement Learning ; 10.48550/arXiv.1911.06854
Zhan, Eric and Tseng, Albert, et el. (2020) Learning Calibratable Policies using Programmatic Style-Consistency ; 10.48550/arXiv.1910.01179
Liu, Yukai and Yu, Rose, et el. (2019) NAOMI: Non-Autoregressive Multiresolution Sequence Imputation ; 10.48550/arXiv.1901.10946
Ghosh, Nikhil and Chen, Yuxin, et el. (2019) Landmark Ordinal Embedding ; 10.48550/arXiv.1910.12379
Verma, Abhinav and Le, Hoang M., et el. (2019) Imitation-Projected Policy Gradient for Programmatic Reinforcement Learning ; 10.48550/arXiv.1907.05431
Jin, Baihong and Tan, Yingshui, et el. (2019) An Encoder-Decoder Based Approach for Anomaly Detection with Application in Additive Manufacturing ; ISBN 978-1-7281-4550-1; 2019 18th IEEE International Conference On Machine Learning And Applications (ICMLA); 1008-1015; 10.1109/ICMLA.2019.00171
Taylor, Andrew J. and Dorobantu, Victor D., et el. (2019) A Control Lyapunov Perspective on Episodic Learning via Projection to State Stability ; ISBN 978-1-7281-1398-2; 2019 IEEE 58th Conference on Decision and Control (CDC); 1448-1455; 10.1109/CDC40024.2019.9029226
Hunziker, Anette and Chen, Yuxin, et el. (2019) Teaching Multiple Concepts to Forgetful Learners ; 10.48550/arXiv.1805.08322
Taylor, Andrew J. and Dorobantu, Victor D., et el. (2019) Episodic Learning with Control Lyapunov Functions for Uncertain Robotic Systems ; ISBN 978-1-7281-4004-9; 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS); 6878-6884; 10.1109/IROS40897.2019.8967820
Song, Jialin and Lanka, Ravi, et el. (2019) Co-training for Policy Learning ; 10.48550/arXiv.1907.04484
Liu, Anqi and Shi, Guanya, et el. (2019) Robust Regression for Safe Exploration in Control ; 10.48550/arXiv.1906.05819
Cheng, Richard and Verma, Abhinav, et el. (2019) Control Regularization for Reduced Variance Reinforcement Learning ; Proceedings of Machine Learning Research; Vol. 97; 1141-1150; 10.48550/arXiv.1905.05380
Ahmadi, Mohamadreza and Wu, Bo, et el. (2019) Barrier Certificates for Assured Machine Teaching ; ISBN 978-1-5386-7926-5; 2019 American Control Conference (ACC); 3658-3663; 10.48550/arXiv.1810.00093
Le, Hoang M. and Voloshin, Cameron, et el. (2019) Batch Policy Learning under Constraints ; Proceedings of Machine Learning Research; Vol. 97; 3703-3712; 10.48550/arXiv.1903.08738
Shi, Guanya and Shi, Xichen, et el. (2019) Neural Lander: Stable Drone Landing Control using Learned Dynamics ; ISBN 978-1-5386-6027-0; 2019 International Conference on Robotics and Automation (ICRA); 9784-9790; 10.1109/ICRA.2019.8794351
Sui, Yanan and Zhuang, Vincent, et el. (2019) Multi-dueling Bandits with Dependent Arms ; 10.48550/arXiv.1705.00253
Yang, Kevin K. and Chen, Yuxin, et el. (2019) Batched Stochastic Bayesian Optimization via Combinatorial Constraints Design ; Proceedings of Machine Learning Research; Vol. 89; 3410-3419; 10.48550/arXiv.1904.08102
Song, Jialin and Chen, Yuxin, et el. (2019) A General Framework for Multi-fidelity Bayesian Optimization with Gaussian Processes ; Proceedings of Machine Learning Research; Vol. 89; 3158-3167; 10.48550/arXiv.1811.00755
Zhou, Jiaji and Ross, Stephane, et el. (2019) Knapsack Constrained Contextual Submodular List Prediction with Application to Multi-document Summarization ; 10.48550/arXiv.1308.3541
Song, Jialin and Lanka, Ravi, et el. (2019) Learning to Search via Retrospective Imitation ; 10.48550/arXiv.1804.00846
Dathathri, Sumanth and Zheng, Stephan, et el. (2019) Detecting Adversarial Examples via Neural Fingerprinting ; 10.48550/arXiv.1803.03870
Sha, Long and Lucey, Patrick, et el. (2019) Fine-Grained Retrieval of Sports Plays using Tree-Based Alignment of Trajectories ; 10.48550/arXiv.1710.02255
Sui, Yanan and Yue, Yisong, et el. (2019) Correlational Dueling Bandits with Application to Clinical Treatment in Large Decision Spaces ; 10.48550/arXiv.1707.02375
Zhan, Eric and Zheng, Stephan, et el. (2019) Generative Multi-Agent Behavioral Cloning ; 10.48550/arXiv.1803.07612
Song, Jialin and Tokpanov, Yury S., et el. (2019) Optimizing Photonic Nanostructures via Multi-fidelity Gaussian Processes ; 10.48550/arXiv.1811.07707
Yu, Rose and Zheng, Stephan, et el. (2019) Long-term Forecasting using Tensor-Train RNNs ; 10.48550/arXiv.1711.00073
Meier, Men-Andrin and Ross, Zachary E., et el. (2019) Reliable Real-time Seismic Signal/Noise Discrimination with Machine Learning ; Journal of Geophysical Research. Solid Earth; Vol. 124; No. 1; 788-800; 10.1029/2018jb016661
Ross, Zachary E. and Yue, Yisong, et el. (2019) PhaseLink: A Deep Learning Approach to Seismic Phase Association ; Journal of Geophysical Research. Solid Earth; Vol. 124; No. 1; 856-869; 10.1029/2018JB016674
Marino, Joseph and Cvitkovic, Milan, et el. (2018) A General Method for Amortizing Variational Filtering ; 10.48550/arXiv.1811.05090
Zheng, Stephan and Yu, Rose, et el. (2018) Multi-resolution Tensor Learning for Large-Scale Spatial Data ; 10.48550/arXiv.1802.06825
Marino, Joseph and Yue, Yisong, et el. (2018) Iterative Amortized Inference ; Proceedings of Machine Learning Research; Vol. 80; 3403-3412; 10.48550/arXiv.1807.09356
Sui, Yanan and Zhuang, Vincent, et el. (2018) Stagewise Safe Bayesian Optimization with Gaussian Processes ; Proceedings of Machine Learning Research; Vol. 80; 4781-4789; 10.48550/arXiv.1806.07555
Mac Aodha, Oisin and Su, Shihan, et el. (2018) Teaching categories to human learners with visual explanations ; ISBN 978-1-5386-6420-9; 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition; 3820-3828; 10.1109/CVPR.2018.00402
Sha, Long and Lucey, Patrick, et el. (2018) Interactive Sports Analytics: An Intelligent Interface for Utilizing Trajectories for Interactive Sports Play Retrieval and Analytics ; ACM Transactions on Computer-Human Interaction; Vol. 25; No. 2; Art. No. 13; 10.1145/3185596
Chen, Yuxin and Mac Aodha, Oisin, et el. (2018) Near-Optimal Machine Teaching via Explanatory Teaching Sets ; Proceedings of Machine Learning Research; Vol. 84; 1970-1978
Zhan, Eric and Zheng, Stephan, et el. (2018) Generating Multi-Agent Trajectories using Programmatic Weak Supervision ; 10.48550/arXiv.1803.07612
Le, Hoang M. and Jiang, Nan, et el. (2018) Hierarchical Imitation and Reinforcement Learning ; Proceedings of Machine Learning Research; Vol. 80; 2917-2926; 10.48550/arXiv.1803.00590
Chen, Yuxin and Singla, Adish, et el. (2018) Understanding the Role of Adaptivity in Machine Teaching: The Case of Version Space Learners ; 10.48550/arXiv.1802.05190
Su, Shihan and Chen, Yuxin, et el. (2017) Interpretable Machine Teaching via Feature Feedback
Le, Hoang M. and Yue, Yisong, et el. (2017) Coordinated Multi-Agent Imitation Learning ; Proceedings of Machine Learning Research; Vol. 70; 1995-2003; 10.48550/arXiv.1703.03121
Deng, Zhiwei and Navarathna, Rajitha, et el. (2017) Factorized Variational Autoencoders for Modeling Audience Reactions to Movies ; ISBN 978-1-5386-0457-1; 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR); 10.1109/CVPR.2017.637
Taylor, Sarah and Kim, Taehwan, et el. (2017) A deep learning approach for generalized speech animation ; ACM Transactions on Graphics; Vol. 36; No. 4; Art. 93; 10.1145/3072959.3073699
Eyjolfsdottir, Eyrun and Branson, Kristin, et el. (2017) Learning recurrent representations for hierarchical behavior modeling ; 10.48550/arXiv.1611.00094
Le, Hoang M. and Carr, Peter, et el. (2017) Data-Driven Ghosting using Deep Imitation Learning
Ruggero Ronchi, Matteo and Kim, Joon Sik, et el. (2016) A Rotation Invariant Latent Factor Model for Moveme Discovery from Static Poses ; ISBN 978-1-5090-5473-2; 16th IEEE International Conference on Data Mining (ICDM); 1179-1184; 10.1109/ICDM.2016.0156
Zheng, Stephan and Yue, Yisong, et el. (2016) Generating Long-term Trajectories Using Deep Hierarchical Networks ; ISBN 9781510838819; Advances in Neural Information Processing Systems (NIPS 2016); 1551-1559; 10.48550/arXiv.1706.07138
Le, Hoang M. and Kang, Andrew, et el. (2016) Smooth Imitation Learning for Online Sequence Prediction ; Proceedings of Machine Learning Research; Vol. 48; 680-688; 10.48550/arXiv.1606.00968
Chen, Jianhui and Le, Hoang M., et el. (2016) Learning Online Smooth Predictors for Realtime Camera Planning using Recurrent Decision Trees ; ISBN 978-1-4673-8851-1; 2016 IEEE Conference on Computer Vision and Pattern Recognition; 4688-4696; 10.1109/CVPR.2016.507
Sha, Long and Lucey, Patrick, et el. (2016) Chalkboarding: A New Spatiotemporal Query Paradigm for Sports Play Retrieval ; ISBN 978-1-4503-4137-0; Proceedings of the 21st International Conference on Intelligent User Interfaces; 336-347; 10.1145/2856767.2856772
Krishnan, Kaushik and Marla, Lavanya, et el. (2016) Robust Ambulance Allocation Using Risk-based Metrics ; ISBN 978-1-4673-9622-6; 2016 8th International Conference on Communication Systems and Networks (COMSNETS); 1-6; 10.1109/COMSNETS.2016.7439958
Liu, Siyuan and Yue, Yisong, et el. (2015) Non-Myopic Adaptive Route Planning in Uncertain Congestion Environments ; IEEE Transactions on Knowledge and Data Engineering; Vol. 27; No. 9; 2438-2451; 10.1109/TKDE.2015.2411278
Kim, Taehwan and Taylor, Sarah, et el. (2015) A Decision Tree Framework for Spatiotemporal Sequence Prediction ; ISBN 978-1-4503-3664-2; Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining; 577-586; 10.1145/2783258.2783356
He, Bryan and Yue, Yisong (2015) Smooth Interactive Submodular Set Cover
Yue, Yisong and Lucey, Patrick, et el. (2014) Learning Fine-Grained Spatial Models for Dynamic Sports Play Prediction ; ISBN 978-1-4799-4274-9; 2014 IEEE International Conference on Data Mining Workshop; 670-679; 10.1109/ICDM.2014.106
Bialkowski, Alina and Lucey, Patrick, et el. (2014) Large-Scale Analysis of Soccer Matches Using Spatiotemporal Tracking Data ; ISBN 978-1-4799-4274-9; 2014 IEEE International Conference on Data Mining Workshop; 725-730; 10.1109/ICDM.2014.133
Bialkowski, Alina and Lucey, Patrick, et el. (2014) Identifying Team Style in Soccer Using Formations Learned from Spatiotemporal Tracking Data ; ISBN 978-1-4799-4274-9; 2014 IEEE International Conference on Data Mining Workshop; 9-14; 10.1109/ICDMW.2014.167
Yue, Yisong and Wang, Chong, et el. (2014) Personalized Collaborative Clustering ; 10.1145/2566486.2567991
Ross, Stephane and Zhou, Jiaji, et el. (2013) Learning Policies for Contextual Submodular Prediction ; Proceedings of Machine Learning Research; Vol. 28; No. 3; 1364-1372; 10.48550/arXiv.1305.2532
Liu, Siyuan and Yue, Yisong, et el. (2013) Adaptive Collective Routing Using Gaussian Process Dynamic Congestion Models ; ISBN 978-1-4503-2174-7; Proceedings of the 19th ACM SIGKDD international Conference on Knowledge Discovery and Data Mining; 704-712; 10.1145/2487575.2487598
Yue, Yisong and Broder, Josef, et el. (2012) The K-armed dueling bandits problem ; Journal of Computer and System Sciences; Vol. 78; No. 5; 1538-1556; 10.1016/j.jcss.2011.12.028
Yue, Yisong and Hong, Sue Ann, et el. (2012) Hierarchical Exploration for Accelerating Contextual Bandits ; ISBN 978-1-4503-1285-1; ICML'12 Proceedings of the 29th International Coference on International Conference on Machine Learning; 979-986; 10.48550/arXiv.1206.6454
Chapelle, Olivier and Joachims, Thorsten, et el. (2012) Large-scale validation and analysis of interleaved search evaluation ; ACM Transactions on Information Systems; Vol. 30; No. 1; Art. No. 6; 10.1145/2094072.2094078
Yue, Yisong and Guestrin, Carlos (2011) Linear Submodular Bandits and their Application to Diversified Retrieval ; ISBN 9781618395993; Advances in Neural Information Processing Systems 24; 1-9
Radlinski, Filip and Yue, Yisong (2011) Practical Online Retrieval Evaluation ; ISBN 978-1-4503-0757-4; Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval; 1301; 10.1145/2009916.2010171
Brandt, Christina and Joachims, Thorsten, et el. (2011) Dynamic Ranked Retrieval ; ISBN 978-1-4503-0493-1; Proceedings of the 4th ACM international conference on Web search and data mining; 247-256; 10.1145/1935826.1935872
Yessenalina, Ainur and Yue, Yisong, et el. (2010) Multi-level structured models for document-level sentiment classification
Yue, Yisong and Gao, Yue, et el. (2010) Learning More Powerful Test Statistics for Click-Based Retrieval Evaluation ; ISBN 978-1-4503-0153-4; Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval; 507-514; 10.1145/1835449.1835534
Yue, Yisong and Patel, Rajan, et el. (2010) Beyond position bias: examining result attractiveness as a source of presentation bias in clickthrough data ; ISBN 978-1-60558-799-8; Proceedings of the 19th international conference on World wide web; 1011-1018; 10.1145/1772690.1772793
Joachims, Thorsten and Hofmann, Thomas, et el. (2009) Predicting Structured Objects with Support Vector Machines ; Communications of the ACM; Vol. 52; No. 11; 97-104; 10.1145/1592761.1592783
Yue, Yisong and Joachims, Thorsten (2009) Interactively Optimizing Information Retrieval Systems as a Dueling Bandits Problem ; ISBN 978-1-60558-516-1; Proceedings of the 26th International Conference on Machine Learning; 1201-1208; 10.1145/1553374.1553527
Yue, Yisong and Joachims, Thorsten (2008) Predicting Diverse Subsets Using Structural SVMs ; ISBN 978-1-60558-205-4; Proceedings of the 25th International Conference on Machine Learning; 1224-1231; 10.1145/1390156.1390310
Yue, Yisong and Finley, Thomas, et el. (2007) A Support Vector Method for Optimizing Average Precision ; ISBN 978-1-59593-597-7; Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval; 271-278; 10.1145/1277741.1277790
