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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661 to 720 of 1,592

Training Deep Learning Models with Norm-Constrained LMOs
Thomas Pethick, Wanyun Xie, Kimon Antonakopoulos +3
cs.LGmath.OCarXiv:2502.07529v22025
Performance of first-order methods for smooth convex minimization: a novel approach
Yoel Drori, Marc Teboulle
math.OCarXiv:1206.3209v12012
Tighter Theory for Local SGD on Identical and Heterogeneous Data
Ahmed Khaled, Konstantin Mishchenko, Peter Richtárik
cs.LGcs.DCmath.NAarXiv:1909.04746v42019
On the Convergence of FedAvg on Non-IID Data
Xiang Li, Kaixuan Huang, Wenhao Yang +2
stat.MLcs.LGmath.OCarXiv:1907.02189v42019
On the Convergence of Adam and Beyond
Sashank J. Reddi, Satyen Kale, Sanjiv Kumar
cs.LGmath.OCstat.MLarXiv:1904.09237v12019
Optimistic mirror descent in saddle-point problems: Going the extra (gradient) mile
Panayotis Mertikopoulos, Bruno Lecouat, Houssam Zenati +3
cs.LGcs.GTmath.OCarXiv:1807.02629v22018
Gradient Descent Provably Optimizes Over-parameterized Neural Networks
Simon S. Du, Xiyu Zhai, Barnabas Poczos +1
cs.LGmath.OCstat.MLarXiv:1810.02054v22018
Parallel Restarted SGD with Faster Convergence and Less Communication: Demystifying Why Model Averaging Works for Deep Learning
Hao Yu, Sen Yang, Shenghuo Zhu
math.OCcs.DCcs.LGarXiv:1807.06629v32018
Active sequential hypothesis testing
Mohammad Naghshvar, Tara Javidi
cs.ITmath.OCmath.STarXiv:1203.4626v42012
On the Global Convergence of Gradient Descent for Over-parameterized Models using Optimal Transport
Lenaic Chizat, Francis Bach
math.OCcs.NEstat.MLarXiv:1805.09545v22018
Distributed Observers Design for Leader-Following Control of Multi-Agent Networks (Extended Version)
Yiguang Hong, Guanrong Chen, Linda Bushnell
math.OCarXiv:1801.00258v12017
How to Escape Saddle Points Efficiently
Chi Jin, Rong Ge, Praneeth Netrapalli +2
cs.LGmath.OCstat.MLarXiv:1703.00887v12017
A First Order Method for Solving Convex Bi-Level Optimization Problems
Shoham Sabach, Shimrit Shtern
math.OCarXiv:1702.03999v12017
Deep Learning without Poor Local Minima
Kenji Kawaguchi
stat.MLcs.LGmath.OCarXiv:1605.07110v32016
Data-driven Distributionally Robust Optimization Using the Wasserstein Metric: Performance Guarantees and Tractable Reformulations
Peyman Mohajerin Esfahani, Daniel Kuhn
math.OCstat.COarXiv:1505.05116v32015
Asynchronous Parallel Stochastic Gradient for Nonconvex Optimization
Xiangru Lian, Yijun Huang, Yuncheng Li +1
math.OCmath.NAstat.MLarXiv:1506.08272v52015
Escaping From Saddle Points --- Online Stochastic Gradient for Tensor Decomposition
Rong Ge, Furong Huang, Chi Jin +1
cs.LGmath.OCstat.MLarXiv:1503.02101v12015
Breaking the Curse of Dimensionality with Convex Neural Networks
Francis Bach
cs.LGmath.OCmath.STarXiv:1412.8690v22014
Making Gradient Descent Optimal for Strongly Convex Stochastic Optimization
Alexander Rakhlin, Ohad Shamir, Karthik Sridharan
cs.LGmath.OCarXiv:1109.5647v72011
Model-free control
Michel Fliess, Cédric Join
math.OCarXiv:1305.7085v22013
Generalized Low Rank Models
Madeleine Udell, Corinne Horn, Reza Zadeh +1
stat.MLcs.LGmath.OCarXiv:1410.0342v42014
Stochastic Primal-Dual Coordinate Method for Regularized Empirical Risk Minimization
Yuchen Zhang, Lin Xiao
math.OCstat.MLarXiv:1409.3257v22014
Minimizing Finite Sums with the Stochastic Average Gradient
Mark Schmidt, Nicolas Le Roux, Francis Bach
math.OCcs.LGstat.COarXiv:1309.2388v22013
Stochastic Gradient Descent, Weighted Sampling, and the Randomized Kaczmarz algorithm
Deanna Needell, Nathan Srebro, Rachel Ward
math.NAcs.CVcs.LGarXiv:1310.5715v52013
A Secure Control Framework for Resource-Limited Adversaries
André Teixeira, Iman Shames, Henrik Sandberg +1
math.OCarXiv:1212.0226v12012
On the Linear Convergence of the Alternating Direction Method of Multipliers
Mingyi Hong, Zhi-Quan Luo
math.OCmath.STarXiv:1208.3922v32012
Synchronization and Power Sharing for Droop-Controlled Inverters in Islanded Microgrids
John W. Simpson-Porco, Florian Dörfler, Francesco Bullo
math.OCeess.SYmath.DSarXiv:1206.5033v32012
Sparse Approximation via Penalty Decomposition Methods
Zhaosong Lu, Yong Zhang
cs.LGmath.OCstat.COarXiv:1205.2334v22012
Distributed Consensus of Linear Multi-Agent Systems with Adaptive Dynamic Protocols
Zhongkui Li, Xiangdong Liu, Wei Ren +1
eess.SYmath.OCarXiv:1109.3838v22011
Optimization with Sparsity-Inducing Penalties
Francis Bach, Rodolphe Jenatton, Julien Mairal +1
cs.LGmath.OCstat.MLarXiv:1108.0775v22011
HOGWILD!: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent
Feng Niu, Benjamin Recht, Christopher Re +1
math.OCcs.LGarXiv:1106.5730v22011
The Convex Geometry of Linear Inverse Problems
Venkat Chandrasekaran, Benjamin Recht, Pablo A. Parrilo +1
math.OCmath.STarXiv:1012.0621v32010
Dual Averaging for Distributed Optimization: Convergence Analysis and Network Scaling
John Duchi, Alekh Agarwal, Martin Wainwright
math.OCeess.SYstat.MLarXiv:1005.2012v32010
Exact finite approximations of average-cost countable Markov Decision Processes
Arie Leizarowitz, Adam Shwartz
math.PRmath.OCarXiv:0711.2185v12007
Latent variable graphical model selection via convex optimization
Venkat Chandrasekaran, Pablo A. Parrilo, Alan S. Willsky
math.STmath.OCarXiv:1008.1290v22010
Muon with Finite Newton-Schulz: The Smoothing Benefit in Nonsmooth Nonconvex Optimization
Mingyi Li, Taira Tsuchiya
cs.LGmath.OCstat.MLarXiv:2608.26288v12026
Provable Edge-of-Stability for Adam on a One-Dimensional Quadratic
Yiman Fong, Heng Yang
cs.LGcs.AImath.OCarXiv:2608.20638v12026
Toward the Optimal Regret-Instability Trade-off in Multi-Armed Bandits
Kaifei Wang, Yinyu Ye, Han Zhong
stat.MLcs.LGmath.OCarXiv:2608.17841v12026
Maximum Tsallis Entropy Distributions for Robust and Efficient Sparse Learning from Correlated Data
Kai Yang, Masoud Asgharian, Celia M. T. Greenwood
math.OCcs.AImath.STarXiv:2608.17244v12026
SOVER: Formal Certification of Optimization Reformulations via LLM-Assisted SMT Verification
Swapnil Bhattacharyya, Mayank Baranwal
cs.AIcs.LGmath.OCarXiv:2609.00728v12026
Multicriteria Optimization and Decision Making: Principles, Algorithms and Case Studies
Michael Emmerich, André Deutz
math.OCmath.NAarXiv:2407.00359v62024
Robust output synchronization of a network of heterogeneous nonlinear agents via nonlinear regulation theory
A. Isidori, L. Marconi, G. Casadei
math.OCarXiv:1303.2804v12013
TEASER: Fast and Certifiable Point Cloud Registration
Heng Yang, Jingnan Shi, Luca Carlone
cs.ROcs.CVmath.OCarXiv:2001.07715v22020
Adaptive Federated Optimization
Sashank Reddi, Zachary Charles, Manzil Zaheer +5
cs.LGcs.DCmath.OCarXiv:2003.00295v52020
Distributed Nonconvex Constrained Optimization over Time-Varying Digraphs
Gesualdo Scutari, Ying Sun
math.OCcs.DCcs.MAarXiv:1809.01106v12018
The Power Grid Library for Benchmarking AC Optimal Power Flow Algorithms
Sogol Babaeinejadsarookolaee, Adam Birchfield, Richard D. Christie +20
math.OCarXiv:1908.02788v22019
A Survey of Optimization Methods from a Machine Learning Perspective
Shiliang Sun, Zehui Cao, Han Zhu +1
cs.LGmath.OCstat.MLarXiv:1906.06821v22019
Formulas for Data-driven Control: Stabilization, Optimality and Robustness
Claudio De Persis, Pietro Tesi
eess.SYmath.OCarXiv:1903.06842v32019
Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers
Zeyuan Allen-Zhu, Yuanzhi Li, Yingyu Liang
cs.LGcs.DScs.NEarXiv:1811.04918v62018
Intelligent Reflecting Surface Enhanced Wireless Network: Joint Active and Passive Beamforming Design
Qingqing Wu, Rui Zhang
cs.ITmath.OCmath.STarXiv:1809.01423v22018
Optimal 3D-Trajectory Design and Resource Allocation for Solar-Powered UAV Communication Systems
Yan Sun, Dongfang Xu, Derrick Wing Kwan Ng +2
cs.ITmath.OCarXiv:1808.00101v12018
Efficient representation and approximation of model predictive control laws via deep learning
Benjamin Karg, Sergio Lucia
math.OCarXiv:1806.10644v32018
Fundamental Tradeoffs in Communication and Trajectory Design for UAV-Enabled Wireless Network
Qingqing Wu, Liang Liu, Rui Zhang
cs.ITmath.DSmath.OCarXiv:1805.07038v12018
Adaptive Federated Learning in Resource Constrained Edge Computing Systems
Shiqiang Wang, Tiffany Tuor, Theodoros Salonidis +4
cs.DCcs.LGmath.OCarXiv:1804.05271v32018
Local Control of Reactive Power by Distributed Photovoltaic Generators
Konstantin S. Turitsyn, Petr Sulc, Scott Backhaus +1
math.OCarXiv:1006.0160v12010
OSQP: An Operator Splitting Solver for Quadratic Programs
Bartolomeo Stellato, Goran Banjac, Paul Goulart +2
math.OCarXiv:1711.08013v42017
Hamilton-Jacobi Reachability: A Brief Overview and Recent Advances
Somil Bansal, Mo Chen, Sylvia Herbert +1
eess.SYmath.DSmath.OCarXiv:1709.07523v12017
Cautious Model Predictive Control using Gaussian Process Regression
Lukas Hewing, Juraj Kabzan, Melanie N. Zeilinger
eess.SYmath.OCarXiv:1705.10702v42017
A Review on Bilevel Optimization: From Classical to Evolutionary Approaches and Applications
Ankur Sinha, Pekka Malo, Kalyanmoy Deb
math.OCcs.NEarXiv:1705.06270v22017
Joint Trajectory and Communication Design for Multi-UAV Enabled Wireless Networks
Qingqing Wu, Yong Zeng, Rui Zhang
cs.ITmath.DSmath.OCarXiv:1705.02723v32017

Optimization and Control

Training Deep Learning Models with Norm-Constrained LMOs

Performance of first-order methods for smooth convex minimization: a novel approach

Tighter Theory for Local SGD on Identical and Heterogeneous Data

On the Convergence of FedAvg on Non-IID Data

On the Convergence of Adam and Beyond

Optimistic mirror descent in saddle-point problems: Going the extra (gradient) mile

Gradient Descent Provably Optimizes Over-parameterized Neural Networks

Parallel Restarted SGD with Faster Convergence and Less Communication: Demystifying Why Model Averaging Works for Deep Learning

Active sequential hypothesis testing

On the Global Convergence of Gradient Descent for Over-parameterized Models using Optimal Transport

Distributed Observers Design for Leader-Following Control of Multi-Agent Networks (Extended Version)

How to Escape Saddle Points Efficiently

A First Order Method for Solving Convex Bi-Level Optimization Problems

Deep Learning without Poor Local Minima

Data-driven Distributionally Robust Optimization Using the Wasserstein Metric: Performance Guarantees and Tractable Reformulations

Asynchronous Parallel Stochastic Gradient for Nonconvex Optimization

Escaping From Saddle Points --- Online Stochastic Gradient for Tensor Decomposition

Breaking the Curse of Dimensionality with Convex Neural Networks

Making Gradient Descent Optimal for Strongly Convex Stochastic Optimization

Model-free control

Generalized Low Rank Models

Stochastic Primal-Dual Coordinate Method for Regularized Empirical Risk Minimization

Minimizing Finite Sums with the Stochastic Average Gradient

Stochastic Gradient Descent, Weighted Sampling, and the Randomized Kaczmarz algorithm

A Secure Control Framework for Resource-Limited Adversaries

On the Linear Convergence of the Alternating Direction Method of Multipliers

Synchronization and Power Sharing for Droop-Controlled Inverters in Islanded Microgrids

Sparse Approximation via Penalty Decomposition Methods

Distributed Consensus of Linear Multi-Agent Systems with Adaptive Dynamic Protocols

Optimization with Sparsity-Inducing Penalties

HOGWILD!: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent

The Convex Geometry of Linear Inverse Problems

Dual Averaging for Distributed Optimization: Convergence Analysis and Network Scaling

Exact finite approximations of average-cost countable Markov Decision Processes

Latent variable graphical model selection via convex optimization

Muon with Finite Newton-Schulz: The Smoothing Benefit in Nonsmooth Nonconvex Optimization

Provable Edge-of-Stability for Adam on a One-Dimensional Quadratic

Toward the Optimal Regret-Instability Trade-off in Multi-Armed Bandits

Maximum Tsallis Entropy Distributions for Robust and Efficient Sparse Learning from Correlated Data

SOVER: Formal Certification of Optimization Reformulations via LLM-Assisted SMT Verification

Multicriteria Optimization and Decision Making: Principles, Algorithms and Case Studies

Robust output synchronization of a network of heterogeneous nonlinear agents via nonlinear regulation theory

TEASER: Fast and Certifiable Point Cloud Registration

Adaptive Federated Optimization

Distributed Nonconvex Constrained Optimization over Time-Varying Digraphs

The Power Grid Library for Benchmarking AC Optimal Power Flow Algorithms

A Survey of Optimization Methods from a Machine Learning Perspective

Formulas for Data-driven Control: Stabilization, Optimality and Robustness

Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers

Intelligent Reflecting Surface Enhanced Wireless Network: Joint Active and Passive Beamforming Design

Optimal 3D-Trajectory Design and Resource Allocation for Solar-Powered UAV Communication Systems

Efficient representation and approximation of model predictive control laws via deep learning

Fundamental Tradeoffs in Communication and Trajectory Design for UAV-Enabled Wireless Network

Adaptive Federated Learning in Resource Constrained Edge Computing Systems

Local Control of Reactive Power by Distributed Photovoltaic Generators

OSQP: An Operator Splitting Solver for Quadratic Programs

Hamilton-Jacobi Reachability: A Brief Overview and Recent Advances

Cautious Model Predictive Control using Gaussian Process Regression

A Review on Bilevel Optimization: From Classical to Evolutionary Approaches and Applications

Joint Trajectory and Communication Design for Multi-UAV Enabled Wireless Networks