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Optimization with Momentum: Dynamical, Control-Theoretic, and Symplectic
  Perspectives
v1v2 (latest)

Optimization with Momentum: Dynamical, Control-Theoretic, and Symplectic Perspectives

Journal of machine learning research (JMLR), 2020
28 February 2020
Michael Muehlebach
Sai Li
ArXiv (abs)PDFHTML

Papers citing "Optimization with Momentum: Dynamical, Control-Theoretic, and Symplectic Perspectives"

28 / 28 papers shown
Stabilizing Policy Gradient Methods via Reward Profiling
Stabilizing Policy Gradient Methods via Reward Profiling
Shihab Ahmed
El Houcine Bergou
A. Dutta
Yue Wang
OffRL
269
0
0
20 Nov 2025
Continuous-Time Analysis of Heavy Ball Momentum in Min-Max Games
Continuous-Time Analysis of Heavy Ball Momentum in Min-Max Games
Yi-Hu Feng
Kaito Fujii
Stratis Skoulakis
Xiao Wang
Volkan Cevher
426
1
0
26 May 2025
Conformal Symplectic Optimization for Stable Reinforcement Learning
Conformal Symplectic Optimization for Stable Reinforcement LearningIEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2024
Yao Lyu
Xiangteng Zhang
Shengbo Eben Li
Jingliang Duan
Letian Tao
Qing Xu
Lei He
Keqiang Li
467
5
0
03 Dec 2024
From exponential to finite/fixed-time stability: Applications to
  optimization
From exponential to finite/fixed-time stability: Applications to optimizationIEEE Conference on Decision and Control (CDC), 2024
Ibrahim Kurban Özaslan
Mihailo R. Jovanović
270
7
0
18 Sep 2024
Generalized Continuous-Time Models for Nesterov's Accelerated Gradient Methods
Generalized Continuous-Time Models for Nesterov's Accelerated Gradient Methods
Chanwoong Park
Youngchae Cho
Insoon Yang
231
1
0
02 Sep 2024
Repelling-Attracting Hamiltonian Monte Carlo
Repelling-Attracting Hamiltonian Monte Carlo
Siddharth Vishwanath
Hyungsuk Tak
270
2
0
07 Mar 2024
Towards a Systems Theory of Algorithms
Towards a Systems Theory of AlgorithmsIEEE Control Systems Letters (L-CSS), 2024
Florian Dorfler
Zhiyu He
Giuseppe Belgioioso
S. Bolognani
John Lygeros
Michael Muehlebach
AI4CE
356
27
0
25 Jan 2024
Gradient Descent with Polyak's Momentum Finds Flatter Minima via Large
  Catapults
Gradient Descent with Polyak's Momentum Finds Flatter Minima via Large Catapults
Prin Phunyaphibarn
Junghyun Lee
Bohan Wang
Huishuai Zhang
Chulhee Yun
365
1
0
25 Nov 2023
Accelerating optimization over the space of probability measures
Accelerating optimization over the space of probability measures
Shi Chen
Wenxuan Wu
Yuhang Yao
Stephen J. Wright
466
12
0
06 Oct 2023
Accelerated Optimization Landscape of Linear-Quadratic Regulator
Accelerated Optimization Landscape of Linear-Quadratic Regulator
Le Feng
Yuan‐Hua Ni
348
1
0
07 Jul 2023
On the connections between optimization algorithms, Lyapunov functions,
  and differential equations: theory and insights
On the connections between optimization algorithms, Lyapunov functions, and differential equations: theory and insightsSIAM Journal on Optimization (SIOPT), 2023
P. Dobson
J. Sanz-Serna
K. Zygalakis
366
7
0
15 May 2023
On Underdamped Nesterov's Acceleration
On Underdamped Nesterov's Acceleration
Shu Chen
Bin Shi
Ya-xiang Yuan
299
5
0
28 Apr 2023
Accelerated First-Order Optimization under Nonlinear Constraints
Accelerated First-Order Optimization under Nonlinear ConstraintsMathematical programming (Math. Program.), 2023
Michael Muehlebach
Michael I. Jordan
564
6
0
01 Feb 2023
Generalized Gradient Flows with Provable Fixed-Time Convergence and Fast
  Evasion of Non-Degenerate Saddle Points
Generalized Gradient Flows with Provable Fixed-Time Convergence and Fast Evasion of Non-Degenerate Saddle PointsIEEE Transactions on Automatic Control (TAC), 2022
Mayank Baranwal
Param Budhraja
V. Raj
A. Hota
281
4
0
07 Dec 2022
Alternating Mirror Descent for Constrained Min-Max Games
Alternating Mirror Descent for Constrained Min-Max GamesNeural Information Processing Systems (NeurIPS), 2022
Andre Wibisono
Molei Tao
Georgios Piliouras
212
23
0
08 Jun 2022
Self-Consistent Dynamical Field Theory of Kernel Evolution in Wide
  Neural Networks
Self-Consistent Dynamical Field Theory of Kernel Evolution in Wide Neural NetworksNeural Information Processing Systems (NeurIPS), 2022
Blake Bordelon
Cengiz Pehlevan
MLT
449
123
0
19 May 2022
A Survey on Distributed Online Optimization and Game
A Survey on Distributed Online Optimization and Game
Xiuxian Li
Lihua Xie
Na Li
OffRL
331
5
0
01 May 2022
Resonance in Weight Space: Covariate Shift Can Drive Divergence of SGD
  with Momentum
Resonance in Weight Space: Covariate Shift Can Drive Divergence of SGD with MomentumInternational Conference on Learning Representations (ICLR), 2022
Kirby Banman
Liam Peet-Paré
N. Hegde
Alona Fyshe
Martha White
255
1
0
22 Mar 2022
Geometric Methods for Sampling, Optimisation, Inference and Adaptive
  Agents
Geometric Methods for Sampling, Optimisation, Inference and Adaptive Agents
Alessandro Barp
Lancelot Da Costa
G. Francca
Karl J. Friston
Mark Girolami
Michael I. Jordan
G. Pavliotis
433
27
0
20 Mar 2022
Born-Infeld (BI) for AI: Energy-Conserving Descent (ECD) for
  Optimization
Born-Infeld (BI) for AI: Energy-Conserving Descent (ECD) for OptimizationInternational Conference on Machine Learning (ICML), 2022
G. Luca
E. Silverstein
233
14
0
26 Jan 2022
Optimization on manifolds: A symplectic approach
Optimization on manifolds: A symplectic approach
G. Francca
Alessandro Barp
Mark Girolami
Sai Li
294
14
0
23 Jul 2021
On Constraints in First-Order Optimization: A View from Non-Smooth
  Dynamical Systems
On Constraints in First-Order Optimization: A View from Non-Smooth Dynamical SystemsJournal of machine learning research (JMLR), 2021
Michael Muehlebach
Sai Li
342
26
0
17 Jul 2021
Revisiting the Role of Euler Numerical Integration on Acceleration and
  Stability in Convex Optimization
Revisiting the Role of Euler Numerical Integration on Acceleration and Stability in Convex OptimizationInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2021
Peiyuan Zhang
Antonio Orvieto
Hadi Daneshmand
Thomas Hofmann
Roy S. Smith
160
11
0
23 Feb 2021
Optimizing Optimizers: Regret-optimal gradient descent algorithms
Optimizing Optimizers: Regret-optimal gradient descent algorithmsAnnual Conference Computational Learning Theory (COLT), 2020
P. Casgrain
Anastasis Kratsios
325
6
0
31 Dec 2020
The connections between Lyapunov functions for some optimization
  algorithms and differential equations
The connections between Lyapunov functions for some optimization algorithms and differential equationsSIAM Journal on Numerical Analysis (SINUM), 2020
J. Sanz-Serna
K. Zygalakis
413
30
0
01 Sep 2020
On dissipative symplectic integration with applications to
  gradient-based optimization
On dissipative symplectic integration with applications to gradient-based optimizationJournal of Statistical Mechanics: Theory and Experiment (JSTAT), 2020
G. Francca
Sai Li
René Vidal
402
48
0
15 Apr 2020
Implicit Regularization and Momentum Algorithms in Nonlinearly
  Parameterized Adaptive Control and Prediction
Implicit Regularization and Momentum Algorithms in Nonlinearly Parameterized Adaptive Control and PredictionNeural Computation (Neural Comput.), 2019
Nicholas M. Boffi
Jean-Jacques E. Slotine
361
46
0
31 Dec 2019
Conformal Symplectic and Relativistic Optimization
Conformal Symplectic and Relativistic Optimization
G. Francca
Jeremias Sulam
Daniel P. Robinson
René Vidal
587
75
0
11 Mar 2019
1
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