Yue, Yisong
- Laubscher, Emily and Wang, Xuefei (Julie), et el. (2024) Accurate single-molecule spot detection for image-based spatial transcriptomics with weakly supervised deep learning; Cell Systems; Vol. 15; No. 5; 475-482.e6; 10.1016/j.cels.2024.04.006
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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