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Mengdi Wang
Mengdi Wang
Center for Statistics & Machine Learning, ECE, Princeton University
Bestätigte E-Mail-Adresse bei princeton.edu - Startseite
Titel
Zitiert von
Zitiert von
Jahr
Sample-optimal parametric q-learning using linearly additive features
L Yang, M Wang
International conference on machine learning, 6995-7004, 2019
3882019
Model-based reinforcement learning with value-targeted regression
A Ayoub, Z Jia, C Szepesvari, M Wang, L Yang
International Conference on Machine Learning, 463-474, 2020
3492020
Reinforcement Learning in Feature Space: Matrix Bandit, Kernels, and Regret Bound
LF Yang, M Wang
International Conference on Machine Learning, 2020, 2019
3422019
Approximation methods for bilevel programming
S Ghadimi, M Wang
arXiv preprint arXiv:1802.02246, 2018
3082018
Stochastic compositional gradient descent: algorithms for minimizing compositions of expected-value functions
M Wang, EX Fang, H Liu
Mathematical Programming 161, 419-449, 2017
2962017
Near-optimal time and sample complexities for solving Markov decision processes with a generative model
A Sidford, M Wang, X Wu, L Yang, Y Ye
Advances in Neural Information Processing Systems 31, 2018
2812018
Visual adversarial examples jailbreak aligned large language models
X Qi, K Huang, A Panda, P Henderson, M Wang, P Mittal
Proceedings of the AAAI conference on artificial intelligence 38 (19), 21527 …, 2024
244*2024
Accelerating stochastic composition optimization
M Wang, J Liu, EX Fang
Journal of Machine Learning Research, 2017, 2016
1722016
Minimax-optimal off-policy evaluation with linear function approximation
Y Duan, Z Jia, M Wang
International Conference on Machine Learning, 2701-2709, 2020
1712020
Variational policy gradient method for reinforcement learning with general utilities
J Zhang, A Koppel, AS Bedi, C Szepesvari, M Wang
Advances in Neural Information Processing Systems 2020, 2020
1682020
Variance reduced value iteration and faster algorithms for solving markov decision processes
A Sidford, M Wang, X Wu, Y Ye.
Proceedings of the Twenty-Ninth Annual ACM-SIAM Symposium on Discrete …, 2017
154*2017
A single timescale stochastic approximation method for nested stochastic optimization
S Ghadimi, A Ruszczynski, M Wang
SIAM Journal on Optimization 30 (1), 960-979, 2020
1412020
Score approximation, estimation and distribution recovery of diffusion models on low-dimensional data
M Chen, K Huang, T Zhao, M Wang
International Conference on Machine Learning, 2024
1352024
Stochastic first-order methods with random constraint projection
M Wang, DP Bertsekas
SIAM Journal on Optimization 26 (1), 681-717, 2016
122*2016
On function approximation in reinforcement learning: Optimism in the face of large state spaces
Z Yang, C Jin, Z Wang, M Wang, MI Jordan
arXiv preprint arXiv:2011.04622, 2020
110*2020
Primal-Dual Learning: Sample Complexity and Sublinear Run Time for Ergodic Markov Decision Problems
M Wang
arXiv preprint arXiv:1710.06100, 2017
98*2017
Finite-sum composition optimization via variance reduced gradient descent
X Lian, M Wang, J Liu
Artificial Intelligence and Statistics. 2017., 2016
982016
Assessing the brittleness of safety alignment via pruning and low-rank modifications
B Wei, K Huang, Y Huang, T Xie, X Qi, M Xia, P Mittal, M Wang, ...
ICML, 2024
902024
Solving discounted stochastic two-player games with near-optimal time and sample complexity
A Sidford, M Wang, L Yang, Y Ye
International Conference on Artificial Intelligence and Statistics, 2992-3002, 2020
862020
Near-optimal offline reinforcement learning with linear representation: Leveraging variance information with pessimism
M Yin, Y Duan, M Wang, YX Wang
arXiv preprint arXiv:2203.05804, 2022
842022
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