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Statistical Learning Theory for Control: A Finite Sample Perspective

Statistical Learning Theory for Control: A Finite Sample Perspective

12 September 2022
Anastasios Tsiamis
Ingvar M. Ziemann
Nikolai Matni
George J. Pappas
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Papers citing "Statistical Learning Theory for Control: A Finite Sample Perspective"

45 / 45 papers shown
Title
Boosting-Enabled Robust System Identification of Partially Observed LTI Systems Under Heavy-Tailed Noise
Boosting-Enabled Robust System Identification of Partially Observed LTI Systems Under Heavy-Tailed Noise
Vinay Kanakeri
Aritra Mitra
19
0
0
25 Apr 2025
Subgradient Method for System Identification with Non-Smooth Objectives
Subgradient Method for System Identification with Non-Smooth Objectives
Baturalp Yalcin
Javad Lavaei
34
0
0
20 Mar 2025
A finite-sample bound for identifying partially observed linear switched systems from a single trajectory
A finite-sample bound for identifying partially observed linear switched systems from a single trajectory
Daniel Racz
M. Petreczky
Bálint Daróczy
50
0
0
17 Mar 2025
Heavy-Tailed Linear Bandits: Huber Regression with One-Pass Update
Jing Wang
Yu-Jie Zhang
Peng Zhao
Zhi-Hua Zhou
51
0
0
01 Mar 2025
Long-Context Linear System Identification
Long-Context Linear System Identification
Oğuz Kaan Yüksel
Mathieu Even
Nicolas Flammarion
16
0
0
08 Oct 2024
Finite Sample Analysis of Distribution-Free Confidence Ellipsoids for
  Linear Regression
Finite Sample Analysis of Distribution-Free Confidence Ellipsoids for Linear Regression
Szabolcs Szentpéteri
Balázs Csanád Csáji
21
0
0
13 Sep 2024
Formal Verification and Control with Conformal Prediction
Formal Verification and Control with Conformal Prediction
Lars Lindemann
Yiqi Zhao
Xinyi Yu
George J. Pappas
Jyotirmoy V. Deshmukh
57
13
0
31 Aug 2024
Exact Recovery Guarantees for Parameterized Nonlinear System Identification Problem under Sparse Disturbances or Semi-Oblivious Attacks
Exact Recovery Guarantees for Parameterized Nonlinear System Identification Problem under Sparse Disturbances or Semi-Oblivious Attacks
Haixiang Zhang
Baturalp Yalcin
Javad Lavaei
Eduardo Sontag
AAML
36
1
0
30 Aug 2024
Causal Learning in Biomedical Applications
Causal Learning in Biomedical Applications
Petr Rysavý
Xiaoyu He
Jakub Marecek
CML
30
1
0
21 Jun 2024
Single Trajectory Conformal Prediction
Single Trajectory Conformal Prediction
Brian Lee
Nikolai Matni
38
2
0
03 Jun 2024
A finite-sample generalization bound for stable LPV systems
A finite-sample generalization bound for stable LPV systems
Daniel Racz
Martin Gonzalez
M. Petreczky
András A. Benczúr
Bálint Daróczy
18
0
0
16 May 2024
Active Learning for Control-Oriented Identification of Nonlinear Systems
Active Learning for Control-Oriented Identification of Nonlinear Systems
Bruce D. Lee
Ingvar M. Ziemann
George J. Pappas
Nikolai Matni
18
5
0
13 Apr 2024
Rate-Optimal Non-Asymptotics for the Quadratic Prediction Error Method
Rate-Optimal Non-Asymptotics for the Quadratic Prediction Error Method
Charis J. Stamouli
Ingvar M. Ziemann
George J. Pappas
16
0
0
11 Apr 2024
Finite Sample Frequency Domain Identification
Finite Sample Frequency Domain Identification
Anastasios Tsiamis
M. Abdalmoaty
Roy S. Smith
John Lygeros
20
0
0
01 Apr 2024
High-dimensional analysis of ridge regression for non-identically distributed data with a variance profile
High-dimensional analysis of ridge regression for non-identically distributed data with a variance profile
Jérémie Bigot
Issa-Mbenard Dabo
Camille Male
29
4
0
29 Mar 2024
From Self-Attention to Markov Models: Unveiling the Dynamics of
  Generative Transformers
From Self-Attention to Markov Models: Unveiling the Dynamics of Generative Transformers
M. E. Ildiz
Yixiao Huang
Yingcong Li
A. S. Rawat
Samet Oymak
16
17
0
21 Feb 2024
Signed-Perturbed Sums Estimation of ARX Systems: Exact Coverage and
  Strong Consistency (Extended Version)
Signed-Perturbed Sums Estimation of ARX Systems: Exact Coverage and Strong Consistency (Extended Version)
A. Carè
E. Weyer
Balázs Cs. Csáji
M. Campi
13
0
0
18 Feb 2024
Sharp Rates in Dependent Learning Theory: Avoiding Sample Size Deflation for the Square Loss
Sharp Rates in Dependent Learning Theory: Avoiding Sample Size Deflation for the Square Loss
Ingvar M. Ziemann
Stephen Tu
George J. Pappas
Nikolai Matni
36
8
0
08 Feb 2024
Nonasymptotic Regret Analysis of Adaptive Linear Quadratic Control with
  Model Misspecification
Nonasymptotic Regret Analysis of Adaptive Linear Quadratic Control with Model Misspecification
Bruce D. Lee
Anders Rantzer
Nikolai Matni
14
6
0
29 Dec 2023
Estimation Sample Complexity of a Class of Nonlinear Continuous-time
  Systems
Estimation Sample Complexity of a Class of Nonlinear Continuous-time Systems
Simon Kuang
Xinfan Lin
15
0
0
08 Dec 2023
Controlgym: Large-Scale Control Environments for Benchmarking
  Reinforcement Learning Algorithms
Controlgym: Large-Scale Control Environments for Benchmarking Reinforcement Learning Algorithms
Xiangyuan Zhang
Weichao Mao
S. Mowlavi
M. Benosman
Tamer Basar
OffRL
AI4CE
19
2
0
30 Nov 2023
Regret Analysis of Learning-Based Linear Quadratic Gaussian Control with
  Additive Exploration
Regret Analysis of Learning-Based Linear Quadratic Gaussian Control with Additive Exploration
Archith Athrey
Othmane Mazhar
Meichen Guo
B. de Schutter
Shengling Shi
14
1
0
05 Nov 2023
From Spectral Theorem to Statistical Independence with Application to
  System Identification
From Spectral Theorem to Statistical Independence with Application to System Identification
Muhammad Naeem
Amir Khazraei
Miroslav Pajic
21
1
0
16 Oct 2023
Learning the Uncertainty Sets for Control Dynamics via Set Membership: A
  Non-Asymptotic Analysis
Learning the Uncertainty Sets for Control Dynamics via Set Membership: A Non-Asymptotic Analysis
Yingying Li
Jing Yu
Lauren Conger
Taylan Kargin
Adam Wierman
21
5
0
26 Sep 2023
A Tutorial on the Non-Asymptotic Theory of System Identification
A Tutorial on the Non-Asymptotic Theory of System Identification
Ingvar M. Ziemann
Anastasios Tsiamis
Bruce D. Lee
Yassir Jedra
Nikolai Matni
George J. Pappas
19
25
0
07 Sep 2023
Preserving Topology of Network Systems: Metric, Analysis, and Optimal
  Design
Preserving Topology of Network Systems: Metric, Analysis, and Optimal Design
Yushan Li
Zitong Wang
Jianping He
Cailian Chen
X. Guan
10
0
0
31 Jul 2023
The noise level in linear regression with dependent data
The noise level in linear regression with dependent data
Ingvar M. Ziemann
Stephen Tu
George J. Pappas
Nikolai Matni
21
5
0
18 May 2023
Exact Recovery for System Identification with More Corrupt Data than
  Clean Data
Exact Recovery for System Identification with More Corrupt Data than Clean Data
Baturalp Yalcin
Haixiang Zhang
Javad Lavaei
Murat Arcak
19
5
0
17 May 2023
Learning and Concentration for High Dimensional Linear Gaussians: an
  Invariant Subspace Approach
Learning and Concentration for High Dimensional Linear Gaussians: an Invariant Subspace Approach
Muhammad Naeem
18
2
0
04 Apr 2023
Stability Bounds for Learning-Based Adaptive Control of Discrete-Time
  Multi-Dimensional Stochastic Linear Systems with Input Constraints
Stability Bounds for Learning-Based Adaptive Control of Discrete-Time Multi-Dimensional Stochastic Linear Systems with Input Constraints
Seth Siriya
Jing Zhu
D. Nešić
Ye Pu
8
0
0
02 Apr 2023
Oracle-Efficient Smoothed Online Learning for Piecewise Continuous
  Decision Making
Oracle-Efficient Smoothed Online Learning for Piecewise Continuous Decision Making
Adam Block
Alexander Rakhlin
Max Simchowitz
21
4
0
10 Feb 2023
Smoothed Online Learning for Prediction in Piecewise Affine Systems
Smoothed Online Learning for Prediction in Piecewise Affine Systems
Adam Block
Max Simchowitz
Russ Tedrake
19
12
0
26 Jan 2023
A New Approach to Learning Linear Dynamical Systems
A New Approach to Learning Linear Dynamical Systems
Ainesh Bakshi
Allen Liu
Ankur Moitra
Morris Yau
16
14
0
23 Jan 2023
Suboptimality analysis of receding horizon quadratic control with
  unknown linear systems and its applications in learning-based control
Suboptimality analysis of receding horizon quadratic control with unknown linear systems and its applications in learning-based control
Shengli Shi
Anastasios Tsiamis
B. de Schutter
12
2
0
19 Jan 2023
Transformers as Algorithms: Generalization and Stability in In-context
  Learning
Transformers as Algorithms: Generalization and Stability in In-context Learning
Yingcong Li
M. E. Ildiz
Dimitris Papailiopoulos
Samet Oymak
13
151
0
17 Jan 2023
A note on the smallest eigenvalue of the empirical covariance of causal
  Gaussian processes
A note on the smallest eigenvalue of the empirical covariance of causal Gaussian processes
Ingvar M. Ziemann
17
3
0
19 Dec 2022
FedSysID: A Federated Approach to Sample-Efficient System Identification
FedSysID: A Federated Approach to Sample-Efficient System Identification
Han Wang
Leonardo F. Toso
James Anderson
FedML
15
17
0
25 Nov 2022
Towards a Theoretical Foundation of Policy Optimization for Learning
  Control Policies
Towards a Theoretical Foundation of Policy Optimization for Learning Control Policies
Bin Hu
K. Zhang
Na Li
M. Mesbahi
Maryam Fazel
Tamer Bacsar
79
27
0
10 Oct 2022
Strong Consistency and Rate of Convergence of Switched Least Squares
  System Identification for Autonomous Markov Jump Linear Systems
Strong Consistency and Rate of Convergence of Switched Least Squares System Identification for Autonomous Markov Jump Linear Systems
Borna Sayedana
Mohammad Afshari
P. Caines
Aditya Mahajan
12
7
0
20 Dec 2021
Stabilizing Dynamical Systems via Policy Gradient Methods
Stabilizing Dynamical Systems via Policy Gradient Methods
Juan C. Perdomo
Jack Umenberger
Max Simchowitz
24
44
0
13 Oct 2021
Minimal Expected Regret in Linear Quadratic Control
Minimal Expected Regret in Linear Quadratic Control
Yassir Jedra
Alexandre Proutière
OffRL
27
17
0
29 Sep 2021
On the Sample Complexity of Stability Constrained Imitation Learning
On the Sample Complexity of Stability Constrained Imitation Learning
Stephen Tu
Alexander Robey
Tingnan Zhang
Nikolai Matni
41
38
0
18 Feb 2021
Linear Convergence of Gradient and Proximal-Gradient Methods Under the
  Polyak-Łojasiewicz Condition
Linear Convergence of Gradient and Proximal-Gradient Methods Under the Polyak-Łojasiewicz Condition
Hamed Karimi
J. Nutini
Mark W. Schmidt
119
1,194
0
16 Aug 2016
Learning without Concentration for General Loss Functions
Learning without Concentration for General Loss Functions
S. Mendelson
55
49
0
13 Oct 2014
Learning without Concentration
Learning without Concentration
S. Mendelson
78
334
0
01 Jan 2014
1