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2008.12776
Cited By
Efficiently Solving MDPs with Stochastic Mirror Descent
International Conference on Machine Learning (ICML), 2020
28 August 2020
Yujia Jin
Aaron Sidford
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Papers citing
"Efficiently Solving MDPs with Stochastic Mirror Descent"
46 / 46 papers shown
Shuffling Heuristic in Variational Inequalities: Establishing New Convergence Guarantees
Daniil Medyakov
Gleb Molodtsov
Grigoriy Evseev
Egor Petrov
Aleksandr Beznosikov
337
3
0
04 Sep 2025
Apprenticeship learning with prior beliefs using inverse optimization
Mauricio Junca
Esteban Leiva
200
0
0
27 May 2025
Layer-wise Quantization for Quantized Optimistic Dual Averaging
Anh Duc Nguyen
Ilia Markov
Frank Zhengqing Wu
Ali Ramezani-Kebrya
Kimon Antonakopoulos
Dan Alistarh
Volkan Cevher
MQ
260
1
0
20 May 2025
Efficiently Solving Discounted MDPs with Predictions on Transition Matrices
Lixing Lyu
Jiashuo Jiang
Wang Chi Cheung
275
3
0
24 Feb 2025
Computing Optimal Regularizers for Online Linear Optimization
Annual Conference Computational Learning Theory (COLT), 2024
Khashayar Gatmiry
Jon Schneider
Stefanie Jegelka
179
3
0
22 Oct 2024
Finding good policies in average-reward Markov Decision Processes without prior knowledge
Adrienne Tuynman
Rémy Degenne
Emilie Kaufmann
272
9
0
27 May 2024
Truncated Variance Reduced Value Iteration
Yujia Jin
Ishani Karmarkar
Aaron Sidford
Jiayi Wang
OffRL
272
7
0
21 May 2024
Stochastic Halpern iteration in normed spaces and applications to reinforcement learning
Mario Bravo
Juan Pablo Contreras
364
9
0
19 Mar 2024
Span-Based Optimal Sample Complexity for Weakly Communicating and General Average Reward MDPs
Neural Information Processing Systems (NeurIPS), 2024
M. Zurek
Yudong Chen
367
11
0
18 Mar 2024
Dealing with unbounded gradients in stochastic saddle-point optimization
Gergely Neu
Nneka Okolo
348
5
0
21 Feb 2024
Scalable and Independent Learning of Nash Equilibrium Policies in
n
n
n
-Player Stochastic Games with Unknown Independent Chains
Tiancheng Qin
S. Rasoul Etesami
300
2
0
04 Dec 2023
Span-Based Optimal Sample Complexity for Average Reward MDPs
M. Zurek
Yudong Chen
290
9
0
22 Nov 2023
Optimal Sample Complexity for Average Reward Markov Decision Processes
International Conference on Learning Representations (ICLR), 2023
Shengbo Wang
Jose H. Blanchet
Peter Glynn
303
15
0
13 Oct 2023
Sharper Model-free Reinforcement Learning for Average-reward Markov Decision Processes
Annual Conference Computational Learning Theory (COLT), 2023
Zihan Zhang
Qiaomin Xie
OffRL
198
25
0
28 Jun 2023
Last-Iterate Convergent Policy Gradient Primal-Dual Methods for Constrained MDPs
Neural Information Processing Systems (NeurIPS), 2023
Dongsheng Ding
Chen-Yu Wei
Jianchao Tan
Alejandro Ribeiro
339
31
0
20 Jun 2023
A Central Limit Theorem for Algorithmic Estimator of Saddle Point
Abhishek Roy
Yian Ma
318
1
0
09 Jun 2023
First Order Methods with Markovian Noise: from Acceleration to Variational Inequalities
Neural Information Processing Systems (NeurIPS), 2023
Aleksandr Beznosikov
S. Samsonov
Marina Sheshukova
Alexander Gasnikov
A. Naumov
Eric Moulines
277
18
0
25 May 2023
Similarity, Compression and Local Steps: Three Pillars of Efficient Communications for Distributed Variational Inequalities
Neural Information Processing Systems (NeurIPS), 2023
Aleksandr Beznosikov
Martin Takáč
Alexander Gasnikov
300
13
0
15 Feb 2023
Optimal Sample Complexity of Reinforcement Learning for Mixing Discounted Markov Decision Processes
Shengbo Wang
Jose H. Blanchet
Peter Glynn
292
7
0
15 Feb 2023
Reducing Blackwell and Average Optimality to Discounted MDPs via the Blackwell Discount Factor
Neural Information Processing Systems (NeurIPS), 2023
Julien Grand-Clément
Marko Petrik
243
22
0
31 Jan 2023
An Efficient Stochastic Algorithm for Decentralized Nonconvex-Strongly-Concave Minimax Optimization
International Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Le‐Yu Chen
Haishan Ye
Luo Luo
503
9
0
05 Dec 2022
Near Sample-Optimal Reduction-based Policy Learning for Average Reward MDP
Jinghan Wang
Meng-Xian Wang
Lin F. Yang
234
25
0
01 Dec 2022
Efficient Global Planning in Large MDPs via Stochastic Primal-Dual Optimization
International Conference on Algorithmic Learning Theory (ALT), 2022
Gergely Neu
Nneka Okolo
371
10
0
21 Oct 2022
Proximal Point Imitation Learning
Neural Information Processing Systems (NeurIPS), 2022
Luca Viano
Angeliki Kamoutsi
Gergely Neu
Igor Krawczuk
Volkan Cevher
457
20
0
22 Sep 2022
Smooth Monotone Stochastic Variational Inequalities and Saddle Point Problems: A Survey
European Mathematical Society Magazine (EMS Magazine), 2022
Aleksandr Beznosikov
Boris Polyak
Eduard A. Gorbunov
D. Kovalev
Alexander Gasnikov
315
33
0
29 Aug 2022
Algorithm for Constrained Markov Decision Process with Linear Convergence
International Conference on Artificial Intelligence and Statistics (AISTATS), 2022
E. Gladin
Maksim Lavrik-Karmazin
K. Zainullina
Varvara Rudenko
Alexander V. Gasnikov
Martin Takáč
250
9
0
03 Jun 2022
Stochastic first-order methods for average-reward Markov decision processes
Mathematics of Operations Research (MOR), 2022
Tianjiao Li
Feiyang Wu
Guanghui Lan
493
23
0
11 May 2022
Solving optimization problems with Blackwell approachability
Mathematics of Operations Research (MOR), 2022
Julien Grand-Clément
Christian Kroer
175
5
0
24 Feb 2022
Optimal Algorithms for Decentralized Stochastic Variational Inequalities
Neural Information Processing Systems (NeurIPS), 2022
D. Kovalev
Aleksandr Beznosikov
Abdurakhmon Sadiev
Michael Persiianov
Peter Richtárik
Alexander Gasnikov
281
38
0
06 Feb 2022
Learning Stationary Nash Equilibrium Policies in
n
n
n
-Player Stochastic Games with Independent Chains
SIAM Journal of Control and Optimization (SICON), 2022
S. Rasoul Etesami
393
9
0
28 Jan 2022
Optimal variance-reduced stochastic approximation in Banach spaces
Wenlong Mou
K. Khamaru
Martin J. Wainwright
Peter L. Bartlett
Sai Li
244
10
0
21 Jan 2022
Efficient Performance Bounds for Primal-Dual Reinforcement Learning from Demonstrations
International Conference on Machine Learning (ICML), 2021
Angeliki Kamoutsi
G. Banjac
John Lygeros
OffRL
191
9
0
28 Dec 2021
Quantum Algorithms for Reinforcement Learning with a Generative Model
Daochen Wang
Aarthi Sundaram
Robin Kothari
Ashish Kapoor
M. Rötteler
209
37
0
15 Dec 2021
Distributed Methods with Compressed Communication for Solving Variational Inequalities, with Theoretical Guarantees
Aleksandr Beznosikov
Peter Richtárik
Michael Diskin
Max Ryabinin
Alexander Gasnikov
FedML
306
22
0
07 Oct 2021
Distributed Saddle-Point Problems Under Similarity
Aleksandr Beznosikov
G. Scutari
Alexander Rogozin
Alexander Gasnikov
425
14
0
22 Jul 2021
Bregman Gradient Policy Optimization
Feihu Huang
Shangqian Gao
Heng-Chiao Huang
433
19
0
23 Jun 2021
Decentralized Local Stochastic Extra-Gradient for Variational Inequalities
Aleksandr Beznosikov
Pavel Dvurechensky
Anastasia Koloskova
V. Samokhin
Sebastian U. Stich
Alexander Gasnikov
299
45
0
15 Jun 2021
Decentralized Personalized Federated Learning for Min-Max Problems
Ekaterina Borodich
Aleksandr Beznosikov
Abdurakhmon Sadiev
V. Sushko
Nikolay Savelyev
Martin Takávc
Alexander Gasnikov
FedML
371
4
0
14 Jun 2021
Towards Tight Bounds on the Sample Complexity of Average-reward MDPs
International Conference on Machine Learning (ICML), 2021
Yujia Jin
Aaron Sidford
112
41
0
13 Jun 2021
Distributionally Robust Optimization with Markovian Data
International Conference on Machine Learning (ICML), 2021
Mengmeng Li
Tobias Sutter
Daniel Kuhn
131
11
0
12 Jun 2021
Reward is enough for convex MDPs
Neural Information Processing Systems (NeurIPS), 2021
Tom Zahavy
Brendan O'Donoghue
Guillaume Desjardins
Satinder Singh
330
81
0
01 Jun 2021
Conic Blackwell Algorithm: Parameter-Free Convex-Concave Saddle-Point Solving
Neural Information Processing Systems (NeurIPS), 2021
Julien Grand-Clément
Christian Kroer
316
5
0
27 May 2021
Near Optimal Policy Optimization via REPS
Neural Information Processing Systems (NeurIPS), 2021
Aldo Pacchiano
Jonathan Lee
Peter L. Bartlett
Ofir Nachum
191
3
0
17 Mar 2021
Primal-Dual Stochastic Mirror Descent for MDPs
International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
D. Tiapkin
Alexander V. Gasnikov
314
7
0
27 Feb 2021
Decentralized Distributed Optimization for Saddle Point Problems
Optimization Methods and Software (OMS), 2021
Alexander Rogozin
Alexander Beznosikov
D. Dvinskikh
D. Kovalev
Pavel Dvurechensky
Alexander Gasnikov
434
25
0
15 Feb 2021
Long-Term Resource Allocation Fairness in Average Markov Decision Process (AMDP) Environment
Adaptive Agents and Multi-Agent Systems (AAMAS), 2021
Ganesh Ghalme
V. Nair
Vishakha Patil
Yilun Zhou
208
6
0
14 Feb 2021
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