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Making Non-Stochastic Control (Almost) as Easy as Stochastic
v1v2 (latest)

Making Non-Stochastic Control (Almost) as Easy as Stochastic

Neural Information Processing Systems (NeurIPS), 2020
10 June 2020
Max Simchowitz
ArXiv (abs)PDFHTML

Papers citing "Making Non-Stochastic Control (Almost) as Easy as Stochastic"

27 / 27 papers shown
Explore-then-Commit for Nonstationary Linear Bandits with Latent Dynamics
Explore-then-Commit for Nonstationary Linear Bandits with Latent Dynamics
Sunmook Choi
Yahya Sattar
Yassir Jedra
Maryam Fazel
Sarah Dean
61
0
0
17 Oct 2025
Online Multi-Agent Control with Adversarial Disturbances
Online Multi-Agent Control with Adversarial Disturbances
Anas Barakat
John Lazarsfeld
Georgios Piliouras
Antonios Varvitsiotis
264
0
0
23 Jun 2025
Tight Rates for Bandit Control Beyond Quadratics
Tight Rates for Bandit Control Beyond QuadraticsNeural Information Processing Systems (NeurIPS), 2024
Y. Jennifer Sun
Zhou Lu
209
2
0
01 Oct 2024
Combining Federated Learning and Control: A Survey
Combining Federated Learning and Control: A Survey
Jakob Weber
Markus Gurtner
A. Lobe
Adrian Trachte
Andreas Kugi
FedMLAI4CE
338
8
0
12 Jul 2024
Online Control in Population Dynamics
Online Control in Population Dynamics
Noah Golowich
Elad Hazan
Zhou Lu
Dhruv Rohatgi
Y. Jennifer Sun
AI4CE
242
3
0
03 Jun 2024
Optimistic Online Non-stochastic Control via FTRL
Optimistic Online Non-stochastic Control via FTRLIEEE Conference on Decision and Control (CDC), 2024
N. Mhaisen
Georgios Iosifidis
217
2
0
04 Apr 2024
Predictive Linear Online Tracking for Unknown Targets
Predictive Linear Online Tracking for Unknown Targets
Anastasios Tsiamis
Aren Karapetyan
Yueshan Li
Efe C. Balta
John Lygeros
448
11
0
15 Feb 2024
Butterfly Effects of SGD Noise: Error Amplification in Behavior Cloning
  and Autoregression
Butterfly Effects of SGD Noise: Error Amplification in Behavior Cloning and AutoregressionInternational Conference on Learning Representations (ICLR), 2023
Adam Block
Dylan J. Foster
Akshay Krishnamurthy
Max Simchowitz
Cyril Zhang
262
11
0
17 Oct 2023
Adaptive Online Non-stochastic Control
Adaptive Online Non-stochastic ControlConference on Learning for Dynamics & Control (L4DC), 2023
N. Mhaisen
Georgios Iosifidis
317
3
0
02 Oct 2023
Online Nonstochastic Model-Free Reinforcement Learning
Online Nonstochastic Model-Free Reinforcement LearningNeural Information Processing Systems (NeurIPS), 2023
Udaya Ghai
Arushi Gupta
Wenhan Xia
Karan Singh
Elad Hazan
OffRL
299
7
0
27 May 2023
Optimal Rates for Bandit Nonstochastic Control
Optimal Rates for Bandit Nonstochastic ControlNeural Information Processing Systems (NeurIPS), 2023
Y. Jennifer Sun
Stephen Newman
Elad Hazan
376
7
0
24 May 2023
Learning to Seek: Multi-Agent Online Source Seeking Against
  Non-Stochastic Disturbances
Learning to Seek: Multi-Agent Online Source Seeking Against Non-Stochastic Disturbances
Bin Du
Kun Qian
Christian G. Claudel
Dengfeng Sun
317
0
0
29 Apr 2023
Best of Both Worlds in Online Control: Competitive Ratio and Policy
  Regret
Best of Both Worlds in Online Control: Competitive Ratio and Policy RegretConference on Learning for Dynamics & Control (L4DC), 2022
Gautam Goel
Naman Agarwal
Karan Singh
Elad Hazan
OffRL
197
13
0
21 Nov 2022
Optimal Dynamic Regret in LQR Control
Optimal Dynamic Regret in LQR ControlNeural Information Processing Systems (NeurIPS), 2022
Dheeraj Baby
Yu Wang
203
18
0
18 Jun 2022
Optimal Competitive-Ratio Control
Optimal Competitive-Ratio Control
Oron Sabag
Sahin Lale
B. Hassibi
228
12
0
03 Jun 2022
Optimal Comparator Adaptive Online Learning with Switching Cost
Optimal Comparator Adaptive Online Learning with Switching CostNeural Information Processing Systems (NeurIPS), 2022
Zhiyu Zhang
Ashok Cutkosky
I. Paschalidis
297
7
0
13 May 2022
Efficient Online Linear Control with Stochastic Convex Costs and Unknown
  Dynamics
Efficient Online Linear Control with Stochastic Convex Costs and Unknown DynamicsAnnual Conference Computational Learning Theory (COLT), 2022
Asaf B. Cassel
Alon Cohen
Google Research
227
5
0
02 Mar 2022
Online Control of Unknown Time-Varying Dynamical Systems
Online Control of Unknown Time-Varying Dynamical SystemsNeural Information Processing Systems (NeurIPS), 2022
Edgar Minasyan
Paula Gradu
Max Simchowitz
Elad Hazan
OffRL
235
34
0
16 Feb 2022
Regret-optimal Estimation and Control
Regret-optimal Estimation and ControlIEEE Transactions on Automatic Control (IEEE TAC), 2021
Gautam Goel
B. Hassibi
171
41
0
22 Jun 2021
Learning from Censored and Dependent Data: The case of Linear Dynamics
Learning from Censored and Dependent Data: The case of Linear DynamicsAnnual Conference Computational Learning Theory (COLT), 2021
Orestis Plevrakis
247
11
0
11 Apr 2021
A Regret Minimization Approach to Iterative Learning Control
A Regret Minimization Approach to Iterative Learning ControlInternational Conference on Machine Learning (ICML), 2021
Naman Agarwal
Elad Hazan
Anirudha Majumdar
Karan Singh
184
14
0
26 Feb 2021
Non-stationary Online Learning with Memory and Non-stochastic Control
Non-stationary Online Learning with Memory and Non-stochastic ControlInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2021
Peng Zhao
Yu-Hu Yan
Yu Wang
Zhi Zhou
525
52
0
07 Feb 2021
Adversarial Tracking Control via Strongly Adaptive Online Learning with
  Memory
Adversarial Tracking Control via Strongly Adaptive Online Learning with MemoryInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2021
Zhiyu Zhang
Ashok Cutkosky
I. Paschalidis
242
16
0
02 Feb 2021
Geometric Exploration for Online Control
Geometric Exploration for Online ControlNeural Information Processing Systems (NeurIPS), 2020
Orestis Plevrakis
Elad Hazan
225
11
0
25 Oct 2020
Black-Box Control for Linear Dynamical Systems
Black-Box Control for Linear Dynamical SystemsAnnual Conference Computational Learning Theory (COLT), 2020
Xinyi Chen
Elad Hazan
262
87
0
13 Jul 2020
Adaptive Regret for Control of Time-Varying Dynamics
Adaptive Regret for Control of Time-Varying DynamicsConference on Learning for Dynamics & Control (L4DC), 2020
Paula Gradu
Elad Hazan
Edgar Minasyan
383
53
0
08 Jul 2020
When is Particle Filtering Efficient for Planning in Partially Observed
  Linear Dynamical Systems?
When is Particle Filtering Efficient for Planning in Partially Observed Linear Dynamical Systems?Conference on Uncertainty in Artificial Intelligence (UAI), 2020
S. Du
Wei Hu
Zhiyuan Li
Ruoqi Shen
Zhao Song
Jiajun Wu
215
1
0
10 Jun 2020
1
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