Wen Sun

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J. Andrew BagnellCarnegie Mellon UniversityVerified email at ri.cmu.edu
Byron BootsAssociate Professor, University of WashingtonVerified email at cs.washington.edu
Arun VenkatramanAurora Innovation / past: Carnegie Mellon UniversityVerified email at cs.cmu.edu
Ron AlterovitzProfessor of Computer Science, University of North Carolina at Chapel HillVerified email at cs.unc.edu
Alekh AgarwalMicrosoft ResearchVerified email at microsoft.com
Geoff GordonProfessor of Machine Learning, Carnegie Mellon UniversityVerified email at cs.cmu.edu
Akshay KrishnamurthyUniversity of Massachusetts AmherstVerified email at cs.umass.edu
Sham M KakadeUniversity of WashingtonVerified email at cs.washington.edu
Nan JiangAssistant Professor of Computer Science, UIUCVerified email at illinois.edu
John LangfordMicrosoft Research New YorkVerified email at hunch.net
martial hebertCMUVerified email at ri.cmu.edu
Jur van den BergIke RoboticsVerified email at ikerobotics.com
Ashish KapoorPartner Research Manager, Microsoft RedmondVerified email at microsoft.com
Siddhartha SrinivasaBoeing Endowed Professor, University of WashingtonVerified email at cs.washington.edu
Zhao SongSchool of Mathematics, Institute for Advanced StudyVerified email at ias.edu
Anirudh VemulaGraduate Student, Robotics Institute, Carnegie Mellon UniversityVerified email at andrew.cmu.edu
MAX SIMCHOWITZUC BerkeleyVerified email at berkeley.edu
Debadeepta DeyPrincipal Researcher, Microsoft ResearchVerified email at microsoft.com
Xuezhou ZhangUniversity of Wisconsin-MadisonVerified email at cs.wisc.edu
Mikael HenaffFacebook AI ResearchVerified email at nyu.edu

Wen Sun

Assistant Professor, Cornell University

Verified email at cornell.edu - Homepage

Machine Learning Motion Planning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Deeply AggreVaTeD: Differentiable Imitation Learning for Sequential Prediction W Sun, A Venkatraman, GJ Gordon, B Boots, JA Bagnell International Conference on Machine Learning, 2017	164	2017
Model-based rl in contextual decision processes: Pac bounds and exponential improvements over model-free approaches W Sun, N Jiang, A Krishnamurthy, A Agarwal, J Langford Conference of Learning Theory (COLT 2019), 2019	76*	2019
High-Frequency Replanning Under Uncertainty Using Parallel Sampling-Based Motion Planning W Sun, S Patil, R Alterovitz IEEE Transactions on Robotics 31 (1), 104 - 116, 2015	61	2015
Stochastic Extended LQR for Optimization-Based Motion Planning Under Uncertainty W Sun, J van den Berg, R Alterovitz IEEE Transactions on Automation Science and Engineering 13 (2), 437-447, 2016	54	2016
Imitation learning as f-divergence minimization L Ke, S Choudhury, M Barnes, W Sun, G Lee, S Srinivasa Algorithmic Foundations of Robotics XIV: Proceedings of the Fourteenth …, 2021	52	2021
Truncated Horizon Policy Search: Combining Reinforcement Learning and Imitation Learning W Sun, JA Bagnell, B Boots International Conference on Learning Representations (ICLR 2018), 2018	50	2018
Dual Policy Iteration W Sun, G Gordon, JA Bagnell, B Boots Advances in Neural Information Processing Systems, 2018	46	2018
Learning to filter with predictive state inference machines W Sun, A Venkatraman, B Boots, JA Bagnell International Conference on Machine Learning, 1197-1205, 2016	43	2016
Provably Efficient Imitation Learning from Observation Alone W Sun, A Vemula, B Boots, JA Bagnell International Conference on Machine Learning, 2019	34	2019
Policy poisoning in batch reinforcement learning and control Y Ma, X Zhang, W Sun, X Zhu arXiv preprint arXiv:1910.05821, 2019	33	2019
Flambe: Structural complexity and representation learning of low rank mdps A Agarwal, S Kakade, A Krishnamurthy, W Sun arXiv preprint arXiv:2006.10814, 2020	32	2020
Corruption robust exploration in episodic reinforcement learning T Lykouris, M Simchowitz, A Slivkins, W Sun arXiv preprint arXiv:1911.08689, 2019	32	2019
Sketching for Kronecker Product Regression and P-splines H Diao, Z Song, W Sun, DP Woodruff International Conference on Artificial Intelligence and Statistics, 2018	30	2018
Safety-aware algorithms for adversarial contextual bandit W Sun, D Dey, A Kapoor International Conference on Machine Learning, 3280-3288, 2017	30	2017
Predictive-state decoders: Encoding the future into recurrent networks A Venkatraman, N Rhinehart, W Sun, L Pinto, M Hebert, B Boots, ... arXiv preprint arXiv:1709.08520, 2017	29	2017
Safe motion planning for imprecise robotic manipulators by minimizing probability of collision W Sun, LG Torres, J Van Den Berg, R Alterovitz Robotics Research, 685-701, 2016	29	2016
Pc-pg: Policy cover directed exploration for provable policy gradient learning A Agarwal, M Henaff, S Kakade, W Sun arXiv preprint arXiv:2007.08459, 2020	28	2020
Disagreement-Regularized Imitation Learning K Brantley, W Sun, M Henaff International Conference on Learning Representations (ICLR 2020), 2020	28	2020
Reinforcement learning: Theory and algorithms A Agarwal, N Jiang, SM Kakade, W Sun CS Dept., UW Seattle, Seattle, WA, USA, Tech. Rep, 2019	23	2019
Efficient model-free reinforcement learning in metric spaces Z Song, W Sun arXiv preprint arXiv:1905.00475, 2019	23	2019

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