Optimization and Control

Papers filed under math.OC on arXiv, each one already summarized by Paperlayer. Open any of them to read the summary beside the original PDF, with every point linked to the line, figure, or table it came from.

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1,441 to 1,500 of 1,592

On Gradient Descent Ascent for Nonconvex-Concave Minimax Problems
Tianyi Lin, Chi Jin, Michael I. Jordan
cs.LGmath.OCstat.MLarXiv:1906.00331v102019
Generative Neural Networks for Sinkhorn Distributionally Robust Hypothesis Testing
Fenglin Zhang, Teyan Liu, Jie Wang
stat.MLcs.LGmath.OCarXiv:2608.22746v12026
Simulation optimization: A review of algorithms and applications
Satyajith Amaran, Nikolaos V. Sahinidis, Bikram Sharda +1
cs.DSmath.OCarXiv:1706.08591v12017
From Relaxed Indexability to Exact Indexability: A $t$-Step Approach for Partially Observable Restless Bandits
Qizhen Jia, Keqin Liu
cs.LGmath.OCarXiv:2608.24167v12026
Katyusha: The First Direct Acceleration of Stochastic Gradient Methods
Zeyuan Allen-Zhu
math.OCcs.DScs.LGarXiv:1603.05953v62016
A splitting algorithm for dual monotone inclusions involving cocoercive operators
Bang Cong Vu
math.OCarXiv:1110.1697v12011
Convergence Rates of Inexact Proximal-Gradient Methods for Convex Optimization
Mark Schmidt, Nicolas Le Roux, Francis Bach
cs.LGmath.OCarXiv:1109.2415v22011
Accelerated Gradient Methods for Nonconvex Nonlinear and Stochastic Programming
Saeed Ghadimi, Guanghui Lan
math.OCarXiv:1310.3787v12013
Learning to Optimize
Ke Li, Jitendra Malik
cs.LGcs.AImath.OCarXiv:1606.01885v12016
Stochastic Gradient Descent for Non-smooth Optimization: Convergence Results and Optimal Averaging Schemes
Ohad Shamir, Tong Zhang
cs.LGmath.OCstat.MLarXiv:1212.1824v22012
Controllability Metrics, Limitations and Algorithms for Complex Networks
Fabio Pasqualetti, Sandro Zampieri, Francesco Bullo
eess.SYmath.OCphysics.data-anarXiv:1308.1201v32013
The Shadow Price of Intelligence: Quality Degradation in LLM Inference as a Supply Chain Problem
Elioth Sanabria
math.OCcs.AIcs.PFarXiv:2608.23986v12026
On the Sample Complexity of the Linear Quadratic Regulator
Sarah Dean, Horia Mania, Nikolai Matni +2
math.OCcs.LGstat.MLarXiv:1710.01688v32017
A Review of Cooperative Multi-Agent Deep Reinforcement Learning
Afshin OroojlooyJadid, Davood Hajinezhad
cs.LGcs.AIcs.MAarXiv:1908.03963v42019
A Practical Guide to Robust Optimization
Bram L. Gorissen, Ihsan Yanıkoğlu, Dick den Hertog
math.OCarXiv:1501.02634v12015
acados: a modular open-source framework for fast embedded optimal control
Robin Verschueren, Gianluca Frison, Dimitris Kouzoupis +7
math.OCarXiv:1910.13753v32019
Stochastic Variance Reduction for Nonconvex Optimization
Sashank J. Reddi, Ahmed Hefny, Suvrit Sra +2
math.OCcs.LGcs.NEarXiv:1603.06160v22016
Levy Flights, Non-local Search and Simulated Annealing
I. Pavlyukevich
cond-mat.stat-mechmath.OCarXiv:cond-mat/0701653v12007
Exact Combinatorial Optimization with Graph Convolutional Neural Networks
Maxime Gasse, Didier Chételat, Nicola Ferroni +2
cs.LGmath.OCstat.MLarXiv:1906.01629v32019
A Variational Perspective on Accelerated Methods in Optimization
Andre Wibisono, Ashia C. Wilson, Michael I. Jordan
math.OCcs.LGstat.MLarXiv:1603.04245v12016
The KL-UCB Algorithm for Bounded Stochastic Bandits and Beyond
Aurélien Garivier, Olivier Cappé
math.STcs.LGeess.SYarXiv:1102.2490v52011
RSA: Byzantine-Robust Stochastic Aggregation Methods for Distributed Learning from Heterogeneous Datasets
Liping Li, Wei Xu, Tianyi Chen +2
cs.LGcs.CRcs.MAarXiv:1811.03761v22018
Phase Recovery, MaxCut and Complex Semidefinite Programming
Irène Waldspurger, Alexandre d'Aspremont, Stéphane Mallat
math.OCarXiv:1206.0102v32012
Risk-Constrained Reinforcement Learning with Percentile Risk Criteria
Yinlam Chow, Mohammad Ghavamzadeh, Lucas Janson +1
cs.AIcs.LGmath.OCarXiv:1512.01629v32015
Distributed convex optimization via continuous-time coordination algorithms with discrete-time communication
Solmaz S. Kia, Jorge Cortes, Sonia Martinez
math.OCarXiv:1401.4432v32014
Alternating Direction Algorithms for Constrained Sparse Regression: Application to Hyperspectral Unmixing
José M. Bioucas-Dias, Mário A. T. Figueiredo
math.OCmath.NAarXiv:1002.4527v22010
Analysis and Control of Epidemics: A survey of spreading processes on complex networks
Cameron Nowzari, Victor M. Preciado, George J. Pappas
math.OCcs.SIphysics.soc-pharXiv:1505.00768v22015
Generalized power method for sparse principal component analysis
Michel Journée, Yurii Nesterov, Peter Richtárik +1
math.OCarXiv:0811.4724v12008
Solving ill-posed inverse problems using iterative deep neural networks
Jonas Adler, Ozan Öktem
math.OCcs.AImath.FAarXiv:1704.04058v22017
Templates for Convex Cone Problems with Applications to Sparse Signal Recovery
Stephen R. Becker, Emmanuel J. Candès, Michael Grant
math.OCmath.NAmath.STarXiv:1009.2065v32010
Robustness of Control Barrier Functions for Safety Critical Control
Xiangru Xu, Paulo Tabuada, Jessy W. Grizzle +1
math.OCeess.SYarXiv:1612.01554v12016
Decentralized event-triggered control over wireless sensor/actuator networks
Manuel Mazo, Paulo Tabuada
math.OCeess.SYarXiv:1004.0477v22010
Fully Decentralized Multi-Agent Reinforcement Learning with Networked Agents
Kaiqing Zhang, Zhuoran Yang, Han Liu +2
cs.LGcs.AIcs.MAarXiv:1802.08757v22018
A Survey of Energy-Efficient Techniques for 5G Networks and Challenges Ahead
Stefano Buzzi, Chih-Lin I, Thierry E. Klein +3
cs.ITcs.NImath.OCarXiv:1604.00786v12016
OpenSCvx: An Open-Source Modular and Extensible Nonlinear Trajectory Planning Package
Christopher R. Hayner, Griffin J. Norris, Fabio Spada +4
cs.ROmath.OCarXiv:2608.21631v12026
Distributed Consensus Algorithms in Sensor Networks: Link Failures and Channel Noise
Soummya Kar, José M. F. Moura
cs.ITcs.MAmath.OCarXiv:0711.3915v22007
Provably Efficient Reinforcement Learning with Linear Function Approximation
Chi Jin, Zhuoran Yang, Zhaoran Wang +1
cs.LGmath.OCstat.MLarXiv:1907.05388v22019
Analysis and Design of Optimization Algorithms via Integral Quadratic Constraints
Laurent Lessard, Benjamin Recht, Andrew Packard
math.OCeess.SYmath.NAarXiv:1408.3595v72014
Stochastic gradient descent on Riemannian manifolds
Silvere Bonnabel
math.OCcs.LGstat.MLarXiv:1111.5280v42011
SARAH: A Novel Method for Machine Learning Problems Using Stochastic Recursive Gradient
Lam M. Nguyen, Jie Liu, Katya Scheinberg +1
stat.MLcs.LGmath.OCarXiv:1703.00102v22017
Optimal Distributed Online Prediction using Mini-Batches
Ofer Dekel, Ran Gilad-Bachrach, Ohad Shamir +1
cs.LGcs.DCmath.OCarXiv:1012.1367v22010
Convergence rates of efficient global optimization algorithms
Adam D. Bull
stat.MLmath.OCmath.STarXiv:1101.3501v32011
Efficient 3-D Placement of an Aerial Base Station in Next Generation Cellular Networks
R. Irem Bor Yaliniz, Amr El-Keyi, Halim Yanikomeroglu
math.OCcs.NIarXiv:1603.00300v12016
Risk-Sensitive Reinforcement Learning with Smoothed Quantile Objectives
Mohammad Alipour-Vaezi, Huaiyang Zhong, Sajad Khodadadian
cs.LGmath.OCarXiv:2608.22227v12026
SGHA: A Single-Loop Fully First-Order Algorithm for Nonconvex-Strongly-Convex Bilevel Optimization
Zhihao Gu, Qilong Wu, Junchi Yang
math.OCcs.LGarXiv:2608.23211v12026
Learning to Control Coupled-Dynamics Environments with Joint Markov Decision Processes
Ege C. Kaya, Aliasghar Pourghani, Mahsa Ghasemi +2
cs.LGmath.OCarXiv:2608.22765v12026
Modern Koopman Theory for Dynamical Systems
Steven L. Brunton, Marko Budišić, Eurika Kaiser +1
math.DScs.LGeess.SYarXiv:2102.12086v22021
A Tour of Reinforcement Learning: The View from Continuous Control
Benjamin Recht
math.OCcs.LGstat.MLarXiv:1806.09460v22018
Consensus of Multi-Agent Systems with General Linear and Lipschitz Nonlinear Dynamics Using Distributed Adaptive Protocols
Zhongkui Li, Wei Ren, Xiangdong Liu +1
eess.SYmath.OCarXiv:1109.3799v12011
On the Convergence of Decentralized Gradient Descent
Kun Yuan, Qing Ling, Wotao Yin
math.OCarXiv:1310.7063v32013
A Proximal Stochastic Gradient Method with Progressive Variance Reduction
Lin Xiao, Tong Zhang
math.OCstat.MLarXiv:1403.4699v12014
A Theoretical Analysis of Deep Q-Learning
Jianqing Fan, Zhaoran Wang, Yuchen Xie +1
cs.LGmath.OCstat.MLarXiv:1901.00137v32019
A Momentum-Based Variance-Reduced Algorithm for Federated Multiobjective Optimization
Yong Zhao, Chunlin You, Minh N. Dao +1
cs.LGmath.OCarXiv:2608.22945v12026
Reinforcement Learning for Combinatorial Optimization: A Survey
Nina Mazyavkina, Sergey Sviridov, Sergei Ivanov +1
cs.LGmath.COmath.OCarXiv:2003.03600v32020
Iteration Complexity of Randomized Block-Coordinate Descent Methods for Minimizing a Composite Function
Peter Richtárik, Martin Takáč
math.OCstat.MLarXiv:1107.2848v12011
Federated Optimization:Distributed Optimization Beyond the Datacenter
Jakub Konečný, Brendan McMahan, Daniel Ramage
cs.LGmath.OCarXiv:1511.03575v12015
Data-Enabled Predictive Control: In the Shallows of the DeePC
Jeremy Coulson, John Lygeros, Florian Dörfler
math.OCarXiv:1811.05890v22018
A Rewriting System for Convex Optimization Problems
Akshay Agrawal, Robin Verschueren, Steven Diamond +1
math.OCcs.MSarXiv:1709.04494v22017
Adaptive Restart for Accelerated Gradient Schemes
Brendan O'Donoghue, Emmanuel Candes
math.OCarXiv:1204.3982v12012
HopSkipJumpAttack: A Query-Efficient Decision-Based Attack
Jianbo Chen, Michael I. Jordan, Martin J. Wainwright
cs.LGcs.CRmath.OCarXiv:1904.02144v52019

Optimization and Control

On Gradient Descent Ascent for Nonconvex-Concave Minimax Problems

Generative Neural Networks for Sinkhorn Distributionally Robust Hypothesis Testing

Simulation optimization: A review of algorithms and applications

From Relaxed Indexability to Exact Indexability: A $t$-Step Approach for Partially Observable Restless Bandits

Katyusha: The First Direct Acceleration of Stochastic Gradient Methods

A splitting algorithm for dual monotone inclusions involving cocoercive operators

Convergence Rates of Inexact Proximal-Gradient Methods for Convex Optimization

Accelerated Gradient Methods for Nonconvex Nonlinear and Stochastic Programming

Learning to Optimize

Stochastic Gradient Descent for Non-smooth Optimization: Convergence Results and Optimal Averaging Schemes

Controllability Metrics, Limitations and Algorithms for Complex Networks

The Shadow Price of Intelligence: Quality Degradation in LLM Inference as a Supply Chain Problem

On the Sample Complexity of the Linear Quadratic Regulator

A Review of Cooperative Multi-Agent Deep Reinforcement Learning

A Practical Guide to Robust Optimization

acados: a modular open-source framework for fast embedded optimal control

Stochastic Variance Reduction for Nonconvex Optimization

Levy Flights, Non-local Search and Simulated Annealing

Exact Combinatorial Optimization with Graph Convolutional Neural Networks

A Variational Perspective on Accelerated Methods in Optimization

The KL-UCB Algorithm for Bounded Stochastic Bandits and Beyond

RSA: Byzantine-Robust Stochastic Aggregation Methods for Distributed Learning from Heterogeneous Datasets

Phase Recovery, MaxCut and Complex Semidefinite Programming

Risk-Constrained Reinforcement Learning with Percentile Risk Criteria

Distributed convex optimization via continuous-time coordination algorithms with discrete-time communication

Alternating Direction Algorithms for Constrained Sparse Regression: Application to Hyperspectral Unmixing

Analysis and Control of Epidemics: A survey of spreading processes on complex networks

Generalized power method for sparse principal component analysis

Solving ill-posed inverse problems using iterative deep neural networks

Templates for Convex Cone Problems with Applications to Sparse Signal Recovery

Robustness of Control Barrier Functions for Safety Critical Control

Decentralized event-triggered control over wireless sensor/actuator networks

Fully Decentralized Multi-Agent Reinforcement Learning with Networked Agents

A Survey of Energy-Efficient Techniques for 5G Networks and Challenges Ahead

OpenSCvx: An Open-Source Modular and Extensible Nonlinear Trajectory Planning Package

Distributed Consensus Algorithms in Sensor Networks: Link Failures and Channel Noise

Provably Efficient Reinforcement Learning with Linear Function Approximation

Analysis and Design of Optimization Algorithms via Integral Quadratic Constraints

Stochastic gradient descent on Riemannian manifolds

SARAH: A Novel Method for Machine Learning Problems Using Stochastic Recursive Gradient

Optimal Distributed Online Prediction using Mini-Batches

Convergence rates of efficient global optimization algorithms

Efficient 3-D Placement of an Aerial Base Station in Next Generation Cellular Networks

Risk-Sensitive Reinforcement Learning with Smoothed Quantile Objectives

SGHA: A Single-Loop Fully First-Order Algorithm for Nonconvex-Strongly-Convex Bilevel Optimization

Learning to Control Coupled-Dynamics Environments with Joint Markov Decision Processes

Modern Koopman Theory for Dynamical Systems

A Tour of Reinforcement Learning: The View from Continuous Control

Consensus of Multi-Agent Systems with General Linear and Lipschitz Nonlinear Dynamics Using Distributed Adaptive Protocols

On the Convergence of Decentralized Gradient Descent

A Proximal Stochastic Gradient Method with Progressive Variance Reduction

A Theoretical Analysis of Deep Q-Learning

A Momentum-Based Variance-Reduced Algorithm for Federated Multiobjective Optimization

Reinforcement Learning for Combinatorial Optimization: A Survey

Iteration Complexity of Randomized Block-Coordinate Descent Methods for Minimizing a Composite Function

Federated Optimization:Distributed Optimization Beyond the Datacenter

Data-Enabled Predictive Control: In the Shallows of the DeePC

A Rewriting System for Convex Optimization Problems

Adaptive Restart for Accelerated Gradient Schemes

HopSkipJumpAttack: A Query-Efficient Decision-Based Attack