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Gradient Descent Learns Linear Dynamical Systems

Gradient Descent Learns Linear Dynamical Systems

16 September 2016
Moritz Hardt
Tengyu Ma
Benjamin Recht
ArXivPDFHTML

Papers citing "Gradient Descent Learns Linear Dynamical Systems"

49 / 49 papers shown
Title
Model-free Online Learning for the Kalman Filter: Forgetting Factor and Logarithmic Regret
Model-free Online Learning for the Kalman Filter: Forgetting Factor and Logarithmic Regret
Jiachen Qian
Yang Zheng
KELM
53
0
0
13 May 2025
Minimisation of Quasar-Convex Functions Using Random Zeroth-Order Oracles
Minimisation of Quasar-Convex Functions Using Random Zeroth-Order Oracles
Amir Ali Farzin
Yuen-Man Pun
Iman Shames
31
0
0
04 May 2025
Expected Variational Inequalities
Expected Variational Inequalities
B. Zhang
Ioannis Anagnostides
Emanuel Tewolde
Ratip Emin Berker
Gabriele Farina
Vincent Conitzer
T. Sandholm
241
0
0
25 Feb 2025
Tuning Frequency Bias of State Space Models
Tuning Frequency Bias of State Space Models
Annan Yu
Dongwei Lyu
S. H. Lim
Michael W. Mahoney
N. Benjamin Erichson
47
3
0
02 Oct 2024
Learning Linear Dynamics from Bilinear Observations
Learning Linear Dynamics from Bilinear Observations
Yahya Sattar
Yassir Jedra
Sarah Dean
34
1
0
24 Sep 2024
Flash STU: Fast Spectral Transform Units
Flash STU: Fast Spectral Transform Units
Y. Isabel Liu
Windsor Nguyen
Yagiz Devre
Evan Dogariu
Anirudha Majumdar
Elad Hazan
AI4TS
72
1
0
16 Sep 2024
Structure learning of Hamiltonians from real-time evolution
Structure learning of Hamiltonians from real-time evolution
Ainesh Bakshi
Allen Liu
Ankur Moitra
Ewin Tang
32
13
0
30 Apr 2024
StableSSM: Alleviating the Curse of Memory in State-space Models through
  Stable Reparameterization
StableSSM: Alleviating the Curse of Memory in State-space Models through Stable Reparameterization
Shida Wang
Qianxiao Li
22
13
0
24 Nov 2023
On the Role of Noise in the Sample Complexity of Learning Recurrent
  Neural Networks: Exponential Gaps for Long Sequences
On the Role of Noise in the Sample Complexity of Learning Recurrent Neural Networks: Exponential Gaps for Long Sequences
A. F. Pour
H. Ashtiani
27
0
0
28 May 2023
Non-Asymptotic Pointwise and Worst-Case Bounds for Classical Spectrum
  Estimators
Non-Asymptotic Pointwise and Worst-Case Bounds for Classical Spectrum Estimators
Andrew G. Lamperski
38
6
0
21 Mar 2023
A Brief Survey on the Approximation Theory for Sequence Modelling
A Brief Survey on the Approximation Theory for Sequence Modelling
Hao Jiang
Qianxiao Li
Zhong Li
Shida Wang
AI4TS
32
12
0
27 Feb 2023
Learning Nonlinear Couplings in Network of Agents from a Single Sample
  Trajectory
Learning Nonlinear Couplings in Network of Agents from a Single Sample Trajectory
Arash A. Amini
Qiyu Sun
N. Motee
31
0
0
20 Nov 2022
Synthetic Blip Effects: Generalizing Synthetic Controls for the Dynamic
  Treatment Regime
Synthetic Blip Effects: Generalizing Synthetic Controls for the Dynamic Treatment Regime
Anish Agarwal
Vasilis Syrgkanis
CML
28
3
0
20 Oct 2022
Zeroth-Order Negative Curvature Finding: Escaping Saddle Points without
  Gradients
Zeroth-Order Negative Curvature Finding: Escaping Saddle Points without Gradients
Hualin Zhang
Huan Xiong
Bin Gu
35
7
0
04 Oct 2022
Statistical Learning Theory for Control: A Finite Sample Perspective
Statistical Learning Theory for Control: A Finite Sample Perspective
Anastasios Tsiamis
Ingvar M. Ziemann
Nikolai Matni
George J. Pappas
28
73
0
12 Sep 2022
Finite Sample Identification of Bilinear Dynamical Systems
Finite Sample Identification of Bilinear Dynamical Systems
Yahya Sattar
Samet Oymak
N. Ozay
32
13
0
29 Aug 2022
On the Convergence to a Global Solution of Shuffling-Type Gradient
  Algorithms
On the Convergence to a Global Solution of Shuffling-Type Gradient Algorithms
Lam M. Nguyen
Trang H. Tran
32
2
0
13 Jun 2022
Sharper Utility Bounds for Differentially Private Models
Sharper Utility Bounds for Differentially Private Models
Yilin Kang
Yong Liu
Jian Li
Weiping Wang
FedML
35
3
0
22 Apr 2022
Escape saddle points by a simple gradient-descent based algorithm
Escape saddle points by a simple gradient-descent based algorithm
Chenyi Zhang
Tongyang Li
ODL
31
15
0
28 Nov 2021
Deep inference of latent dynamics with spatio-temporal super-resolution
  using selective backpropagation through time
Deep inference of latent dynamics with spatio-temporal super-resolution using selective backpropagation through time
Feng Zhu
Andrew R. Sedler
Harrison A. Grier
Nauman Ahad
Mark A. Davenport
Matthew T. Kaufman
Andrea Giovannucci
C. Pandarinath
30
10
0
29 Oct 2021
Improved Learning Rates for Stochastic Optimization: Two Theoretical
  Viewpoints
Improved Learning Rates for Stochastic Optimization: Two Theoretical Viewpoints
Shaojie Li
Yong Liu
26
13
0
19 Jul 2021
Stochastic Polyak Stepsize with a Moving Target
Stochastic Polyak Stepsize with a Moving Target
Robert Mansel Gower
Aaron Defazio
Michael G. Rabbat
32
17
0
22 Jun 2021
Metric Entropy Limits on Recurrent Neural Network Learning of Linear
  Dynamical Systems
Metric Entropy Limits on Recurrent Neural Network Learning of Linear Dynamical Systems
Clemens Hutter
R. Gül
Helmut Bölcskei
21
9
0
06 May 2021
Almost Surely Stable Deep Dynamics
Almost Surely Stable Deep Dynamics
Nathan P. Lawrence
Philip D. Loewen
M. Forbes
Johan U. Backstrom
R. Bhushan Gopaluni
BDL
40
20
0
26 Mar 2021
On Riemannian Stochastic Approximation Schemes with Fixed Step-Size
On Riemannian Stochastic Approximation Schemes with Fixed Step-Size
Alain Durmus
P. Jiménez
Eric Moulines
Salem Said
29
12
0
15 Feb 2021
Task-Optimal Exploration in Linear Dynamical Systems
Task-Optimal Exploration in Linear Dynamical Systems
Andrew Wagenmaker
Max Simchowitz
Kevin G. Jamieson
22
18
0
10 Feb 2021
A Study of Condition Numbers for First-Order Optimization
A Study of Condition Numbers for First-Order Optimization
Charles Guille-Escuret
Baptiste Goujaud
M. Girotti
Ioannis Mitliagkas
6
18
0
10 Dec 2020
Improved rates for prediction and identification of partially observed
  linear dynamical systems
Improved rates for prediction and identification of partially observed linear dynamical systems
Holden Lee
21
10
0
19 Nov 2020
SLIP: Learning to Predict in Unknown Dynamical Systems with Long-Term
  Memory
SLIP: Learning to Predict in Unknown Dynamical Systems with Long-Term Memory
Paria Rashidinejad
Jiantao Jiao
Stuart J. Russell
26
11
0
12 Oct 2020
SGD for Structured Nonconvex Functions: Learning Rates, Minibatching and
  Interpolation
SGD for Structured Nonconvex Functions: Learning Rates, Minibatching and Interpolation
Robert Mansel Gower
Othmane Sebbouh
Nicolas Loizou
25
74
0
18 Jun 2020
Active Learning for Nonlinear System Identification with Guarantees
Active Learning for Nonlinear System Identification with Guarantees
Horia Mania
Michael I. Jordan
Benjamin Recht
41
101
0
18 Jun 2020
Active Learning for Identification of Linear Dynamical Systems
Active Learning for Identification of Linear Dynamical Systems
Andrew Wagenmaker
Kevin G. Jamieson
27
46
0
02 Feb 2020
Natural Actor-Critic Converges Globally for Hierarchical Linear
  Quadratic Regulator
Natural Actor-Critic Converges Globally for Hierarchical Linear Quadratic Regulator
Yuwei Luo
Zhuoran Yang
Zhaoran Wang
Mladen Kolar
26
9
0
14 Dec 2019
Actor-Critic Provably Finds Nash Equilibria of Linear-Quadratic
  Mean-Field Games
Actor-Critic Provably Finds Nash Equilibria of Linear-Quadratic Mean-Field Games
Zuyue Fu
Zhuoran Yang
Yongxin Chen
Zhaoran Wang
24
54
0
16 Oct 2019
The Error-Feedback Framework: Better Rates for SGD with Delayed
  Gradients and Compressed Communication
The Error-Feedback Framework: Better Rates for SGD with Delayed Gradients and Compressed Communication
Sebastian U. Stich
Sai Praneeth Karimireddy
FedML
25
20
0
11 Sep 2019
On the Global Convergence of Actor-Critic: A Case for Linear Quadratic
  Regulator with Ergodic Cost
On the Global Convergence of Actor-Critic: A Case for Linear Quadratic Regulator with Ergodic Cost
Zhuoran Yang
Yongxin Chen
Mingyi Hong
Zhaoran Wang
32
39
0
14 Jul 2019
From self-tuning regulators to reinforcement learning and back again
From self-tuning regulators to reinforcement learning and back again
Nikolai Matni
Alexandre Proutiere
Anders Rantzer
Stephen Tu
27
88
0
27 Jun 2019
On the Global Convergence of Imitation Learning: A Case for Linear
  Quadratic Regulator
On the Global Convergence of Imitation Learning: A Case for Linear Quadratic Regulator
Qi Cai
Mingyi Hong
Yongxin Chen
Zhaoran Wang
27
34
0
11 Jan 2019
On the Convergence Rate of Training Recurrent Neural Networks
On the Convergence Rate of Training Recurrent Neural Networks
Zeyuan Allen-Zhu
Yuanzhi Li
Zhao Song
32
191
0
29 Oct 2018
Continuous-time Models for Stochastic Optimization Algorithms
Continuous-time Models for Stochastic Optimization Algorithms
Antonio Orvieto
Aurelien Lucchi
19
31
0
05 Oct 2018
Non-asymptotic Identification of LTI Systems from a Single Trajectory
Non-asymptotic Identification of LTI Systems from a Single Trajectory
Samet Oymak
N. Ozay
21
221
0
14 Jun 2018
Gradient Descent for One-Hidden-Layer Neural Networks: Polynomial
  Convergence and SQ Lower Bounds
Gradient Descent for One-Hidden-Layer Neural Networks: Polynomial Convergence and SQ Lower Bounds
Santosh Vempala
John Wilmes
MLT
22
50
0
07 May 2018
Model-Free Linear Quadratic Control via Reduction to Expert Prediction
Model-Free Linear Quadratic Control via Reduction to Expert Prediction
Yasin Abbasi-Yadkori
N. Lazić
Csaba Szepesvári
OffRL
13
94
0
17 Apr 2018
Spectral Filtering for General Linear Dynamical Systems
Spectral Filtering for General Linear Dynamical Systems
Elad Hazan
Holden Lee
Karan Singh
Cyril Zhang
Yi Zhang
47
97
0
12 Feb 2018
SGD Learns Over-parameterized Networks that Provably Generalize on
  Linearly Separable Data
SGD Learns Over-parameterized Networks that Provably Generalize on Linearly Separable Data
Alon Brutzkus
Amir Globerson
Eran Malach
Shai Shalev-Shwartz
MLT
50
276
0
27 Oct 2017
On the Sample Complexity of the Linear Quadratic Regulator
On the Sample Complexity of the Linear Quadratic Regulator
Sarah Dean
Horia Mania
Nikolai Matni
Benjamin Recht
Stephen Tu
40
570
0
04 Oct 2017
Non-Asymptotic Analysis of Robust Control from Coarse-Grained
  Identification
Non-Asymptotic Analysis of Robust Control from Coarse-Grained Identification
Stephen Tu
Ross Boczar
A. Packard
Benjamin Recht
11
69
0
15 Jul 2017
Kronecker Recurrent Units
Kronecker Recurrent Units
C. Jose
Moustapha Cissé
F. Fleuret
ODL
24
45
0
29 May 2017
Training Deep Networks without Learning Rates Through Coin Betting
Training Deep Networks without Learning Rates Through Coin Betting
Francesco Orabona
Tatiana Tommasi
ODL
26
4
0
22 May 2017
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