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
Geoff GordonProfessor of Machine Learning, Carnegie Mellon UniversityVerified email at cs.cmu.edu
Akshay KrishnamurthyUniversity of Massachusetts AmherstVerified email at cs.umass.edu
Alekh AgarwalMicrosoft ResearchVerified email at microsoft.com
John LangfordMicrosoft Research New YorkVerified email at hunch.net
martial hebertCMUVerified email at ri.cmu.edu
Ashish KapoorPartner Research Manager, Microsoft RedmondVerified email at microsoft.com
Jur van den BergIke RoboticsVerified email at ikerobotics.com
Sham M KakadeUniversity of WashingtonVerified email at cs.washington.edu
Nan JiangAssistant Professor of Computer Science, UIUCVerified email at illinois.edu
Siddhartha SrinivasaBoeing Endowed Professor, University of WashingtonVerified email at cs.washington.edu
Anirudh VemulaGraduate Student, Robotics Institute, Carnegie Mellon UniversityVerified email at andrew.cmu.edu
Zhao SongSchool of Mathematics, Institute for Advanced StudyVerified email at ias.edu
Debadeepta DeyPrincipal Researcher, Microsoft ResearchVerified email at microsoft.com
MAX SIMCHOWITZUC BerkeleyVerified email at berkeley.edu
Mikael HenaffFacebook AI ResearchVerified email at nyu.edu
Huaian DiaoSchool of Mathematics and Statistics, Northeast Normal UniversityVerified email at nenu.edu.cn

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	153	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	66*	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	58	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	49	2016
Truncated Horizon Policy Search: Combining Reinforcement Learning and Imitation Learning W Sun, JA Bagnell, B Boots International Conference on Learning Representations (ICLR 2018), 2018	45	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	42	2016
Dual Policy Iteration W Sun, G Gordon, JA Bagnell, B Boots Advances in Neural Information Processing Systems, 2018	41	2018
Imitation Learning as -Divergence Minimization L Ke, M Barnes, W Sun, G Lee, S Choudhury, S Srinivasa arXiv preprint arXiv:1905.12888, 2019	36	2019
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	30	2017
Provably Efficient Imitation Learning from Observation Alone W Sun, A Vemula, B Boots, JA Bagnell International Conference on Machine Learning, 2019	29	2019
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	28	2016
Policy poisoning in batch reinforcement learning and control Y Ma, X Zhang, W Sun, X Zhu arXiv preprint arXiv:1910.05821, 2019	27	2019
Safety-aware algorithms for adversarial contextual bandit W Sun, D Dey, A Kapoor International Conference on Machine Learning, 3280-3288, 2017	26	2017
Sketching for Kronecker Product Regression and P-splines H Diao, Z Song, W Sun, DP Woodruff International Conference on Artificial Intelligence and Statistics, 2018	24	2018
Disagreement-Regularized Imitation Learning K Brantley, W Sun, M Henaff International Conference on Learning Representations (ICLR 2020), 2020	22	2020
Corruption robust exploration in episodic reinforcement learning T Lykouris, M Simchowitz, A Slivkins, W Sun arXiv preprint arXiv:1911.08689, 2019	20	2019
Contrasting Exploration in Parameter and Action Space: A Zeroth-Order Optimization Perspective A Vemula, W Sun, JA Bagnell International Conference on Artificial Intelligence and Statistics, 2019	20	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	19	2020
Efficient model-free reinforcement learning in metric spaces Z Song, W Sun arXiv preprint arXiv:1905.00475, 2019	16	2019
Motion planning under uncertainty for medical needle steering using optimization in belief space W Sun, R Alterovitz 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2014	14	2014

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