Παρακολούθηση
Wen Sun
Wen Sun
Assistant Professor, Cornell University
Η διεύθυνση ηλεκτρονικού ταχυδρομείου έχει επαληθευτεί στον τομέα cornell.edu - Αρχική σελίδα
Τίτλος
Παρατίθεται από
Παρατίθεται από
Έτος
Reinforcement learning: Theory and algorithms
A Agarwal, N Jiang, SM Kakade, W Sun
CS Dept., UW Seattle, Seattle, WA, USA, Tech. Rep 32, 96, 2019
3302019
Flambe: Structural complexity and representation learning of low rank mdps
A Agarwal, S Kakade, A Krishnamurthy, W Sun
Advances in neural information processing systems 33, 20095-20107, 2020
2962020
Deeply AggreVaTeD: Differentiable Imitation Learning for Sequential Prediction
W Sun, A Venkatraman, GJ Gordon, B Boots, JA Bagnell
International Conference on Machine Learning, 2017
2862017
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
2802019
Bilinear classes: A structural framework for provable generalization in rl
S Du, S Kakade, J Lee, S Lovett, G Mahajan, W Sun, R Wang
International Conference on Machine Learning, 2826-2836, 2021
2442021
Pessimistic model-based offline reinforcement learning under partial coverage
M Uehara, W Sun
arXiv preprint arXiv:2107.06226, 2021
187*2021
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
1752021
Representation learning for online and offline rl in low-rank mdps
M Uehara, X Zhang, W Sun
arXiv preprint arXiv:2110.04652, 2021
1572021
Information theoretic regret bounds for online nonlinear control
S Kakade, A Krishnamurthy, K Lowrey, M Ohnishi, W Sun
Advances in Neural Information Processing Systems 33, 15312-15325, 2020
1472020
Pc-pg: Policy cover directed exploration for provable policy gradient learning
A Agarwal, M Henaff, S Kakade, W Sun
Advances in neural information processing systems 33, 13399-13412, 2020
1462020
Corruption-robust exploration in episodic reinforcement learning
T Lykouris, M Simchowitz, A Slivkins, W Sun
Conference on Learning Theory, 3242-3245, 2021
1312021
Policy poisoning in batch reinforcement learning and control
Y Ma, X Zhang, W Sun, J Zhu
Advances in Neural Information Processing Systems 32, 2019
1282019
Disagreement-Regularized Imitation Learning
K Brantley, W Sun, M Henaff
International Conference on Learning Representations (ICLR 2020), 2020
1222020
Provably Efficient Imitation Learning from Observation Alone
W Sun, A Vemula, B Boots, JA Bagnell
International Conference on Machine Learning, 2019
1122019
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
1092015
Truncated Horizon Policy Search: Combining Reinforcement Learning and Imitation Learning
W Sun, JA Bagnell, B Boots
International Conference on Learning Representations (ICLR 2018), 2018
1072018
Mitigating covariate shift in imitation learning via offline data with partial coverage
J Chang, M Uehara, D Sreenivas, R Kidambi, W Sun
Advances in Neural Information Processing Systems 34, 965-979, 2021
1042021
Multi-robot collision avoidance under uncertainty with probabilistic safety barrier certificates
W Luo, W Sun, A Kapoor
Advances in Neural Information Processing Systems 33, 372-383, 2020
932020
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
932016
Hybrid rl: Using both offline and online data can make rl efficient
Y Song, Y Zhou, A Sekhari, JA Bagnell, A Krishnamurthy, W Sun
arXiv preprint arXiv:2210.06718, 2022
862022
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