Yunhao Tang
Yunhao Tang
PhD student, Columbia University
Verified email at columbia.edu - Homepage
Title
Cited by
Cited by
Year
ES-MAML: Simple Hessian-Free Meta Learning
X Song, W Gao, Y Yang, K Choromanski, A Pacchiano, Y Tang
arXiv preprint arXiv:1910.01215, 2019
232019
Discretizing continuous action space for on-policy optimization
Y Tang, S Agrawal
Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 5981-5988, 2020
202020
Reinforcement learning for integer programming: Learning to cut
Y Tang, S Agrawal, Y Faenza
International Conference on Machine Learning, 9367-9376, 2020
182020
Provably robust blackbox optimization for reinforcement learning
K Choromanski, A Pacchiano, J Parker-Holder, Y Tang, D Jain, Y Yang, ...
CoRR, abs/1903.02993, 2019
17*2019
From complexity to simplicity: Adaptive es-active subspaces for blackbox optimization
KM Choromanski, A Pacchiano, J Parker-Holder, Y Tang, V Sindhwani
Advances in Neural Information Processing Systems, 10299-10309, 2019
172019
Exploration by Distributional Reinforcement Learning
Y Tang, S Agrawal
arXiv preprint arXiv:1805.01907, 2018
172018
Boosting Trust Region Policy Optimization by Normalizing Flows Policy
Y Tang, S Agrawal
arXiv preprint arXiv:1809.10326, 2018
112018
Orthogonal Estimation of Wasserstein Distances
M Rowland, J Hron, Y Tang, K Choromanski, T Sarlos, A Weller
arXiv preprint arXiv:1903.03784, 2019
82019
Implicit Policy for Reinforcement Learning
Y Tang, S Agrawal
arXiv preprint arXiv:1806.06798, 2018
72018
Variational Deep Q Network
Y Tang, A Kucukelbir
arXiv preprint arXiv:1711.11225, 2017
72017
KAMA-NNs: low-dimensional rotation based neural networks
K Choromanski, A Pacchiano, J Pennington, Y Tang
The 22nd International Conference on Artificial Intelligence and Statistics …, 2019
52019
Learning to Score Behaviors for Guided Policy Optimization
A Pacchiano, J Parker-Holder, Y Tang, A Choromanska, K Choromanski, ...
arXiv preprint arXiv:1906.04349, 2019
4*2019
Monte-Carlo tree search as regularized policy optimization
JB Grill, F Altché, Y Tang, T Hubert, M Valko, I Antonoglou, R Munos
International Conference on Machine Learning, 3769-3778, 2020
32020
Variance reduction for evolution strategies via structured control variates
Y Tang, K Choromanski, A Kucukelbir
International Conference on Artificial Intelligence and Statistics, 646-656, 2020
32020
Discrete Action On-Policy Learning with Action-Value Critic
Y Yue, Y Tang, M Yin, M Yin
arXiv preprint arXiv:2002.03534, 2020
32020
Self-imitation learning via generalized lower bound q-learning
Y Tang
Advances in Neural Information Processing Systems 33, 2020
32020
Online Hyper-parameter Tuning in Off-policy Learning via Evolutionary Strategies
Y Tang, K Choromanski
arXiv preprint arXiv:2006.07554, 2020
12020
Taylor expansion policy optimization
Y Tang, M Valko, R Munos
arXiv preprint arXiv:2003.06259, 2020
12020
Reinforcement Learning with Chromatic Networks
X Song, K Choromanski, J Parker-Holder, Y Tang, W Gao, A Pacchiano, ...
arXiv preprint arXiv:1907.06511, 2019
12019
Structured Monte Carlo Sampling for Nonisotropic Distributions via Determinantal Point Processes
K Choromanski, A Pacchiano, J Parker-Holder, Y Tang
arXiv preprint arXiv:1905.12667, 2019
12019
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Articles 1–20