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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1,621 to 1,680 of 2,617

Online Placement of Multi-Component Applications in Edge Computing Environments
Shiqiang Wang, Murtaza Zafer, Kin K. Leung
cs.DCcs.DScs.NIarXiv:1605.08023v22016
Global Optimality in Low-rank Matrix Optimization
Zhihui Zhu, Qiuwei Li, Gongguo Tang +1
cs.ITmath.OCarXiv:1702.07945v32017
A Convex Optimization Approach for Finite-Thrust Time-Constrained Cooperative Rendezvous
Boris Benedikter, Alessandro Zavoli, Guido Colasurdo
math.OCarXiv:1909.09443v12019
A survey on high-dimensional Gaussian process modeling with application to Bayesian optimization
Mickael Binois, Nathan Wycoff
math.OCarXiv:2111.05040v22021
Sequence Set Design With Good Correlation Properties via Majorization-Minimization
Junxiao Song, Prabhu Babu, Daniel P. Palomar
math.OCarXiv:1510.01899v12015
Learning Model Predictive Control for iterative tasks. A Data-Driven Control Framework
Ugo Rosolia, Francesco Borrelli
eess.SYcs.LGmath.OCarXiv:1609.01387v72016
Lions and Muons: Optimization via Stochastic Frank-Wolfe under Heavy-Tailed Noise
Maria-Eleni Sfyraki, Jun-Kun Wang
math.OCstat.MLarXiv:2506.04192v42025
Hyperspectral Unmixing Overview: Geometrical, Statistical, and Sparse Regression-Based Approaches
José M. Bioucas-Dias, Antonio Plaza, Nicolas Dobigeon +4
physics.data-anmath.OCstat.AParXiv:1202.6294v22012
Graduated Non-Convexity for Robust Spatial Perception: From Non-Minimal Solvers to Global Outlier Rejection
Heng Yang, Pasquale Antonante, Vasileios Tzoumas +1
cs.CVcs.ROmath.OCarXiv:1909.08605v42019
New Analysis and Results for the Frank-Wolfe Method
Robert M. Freund, Paul Grigas
math.OCarXiv:1307.0873v22013
The Augmented Lagrange Multiplier Method for Exact Recovery of Corrupted Low-Rank Matrices
Zhouchen Lin, Minming Chen, Yi Ma
math.OCeess.SYmath.NAarXiv:1009.5055v32010
Average-Cost Markov Decision Processes with Weakly Continuous Transition Probabilities
Eugene A. Feinberg, Pavlo O. Kasyanov, Nina V. Zadoianchuk
math.OCarXiv:1202.4122v12012
Formulas for Data-driven Control: Stabilization, Optimality and Robustness
Claudio De Persis, Pietro Tesi
eess.SYmath.OCarXiv:1903.06842v32019
Federated Expectation Maximization with heterogeneity mitigation and variance reduction
Aymeric Dieuleveut, Gersende Fort, Eric Moulines +1
math.OCcs.AIcs.LGarXiv:2111.02083v22021
Distributed Optimal Power Flow Algorithm for Balanced Radial Distribution Networks
Qiuyu Peng, Steven H. Low
math.OCarXiv:1404.0700v22014
On Nonconvex Decentralized Gradient Descent
Jinshan Zeng, Wotao Yin
math.OCcs.DCcs.MAarXiv:1608.05766v42016
Distributed Reinforcement Learning for Decentralized Linear Quadratic Control: A Derivative-Free Policy Optimization Approach
Yingying Li, Yujie Tang, Runyu Zhang +1
eess.SYcs.LGcs.SYarXiv:1912.09135v32019
Decentralized Deep Learning with Arbitrary Communication Compression
Anastasia Koloskova, Tao Lin, Sebastian U. Stich +1
cs.LGcs.DCcs.DSarXiv:1907.09356v32019
On TD(0) with function approximation: Concentration bounds and a centered variant with exponential convergence
Nathaniel Korda, L. A. Prashanth
cs.LGmath.OCstat.MLarXiv:1411.3224v22014
Non-square matrix sensing without spurious local minima via the Burer-Monteiro approach
Dohyung Park, Anastasios Kyrillidis, Constantine Caramanis +1
stat.MLcs.ITcs.LGarXiv:1609.03240v22016
Combining Prior Knowledge and Data for Robust Controller Design
Julian Berberich, Carsten W. Scherer, Frank Allgöwer
eess.SYmath.OCarXiv:2009.05253v42020
Hessian Riemannian gradient flows in convex programming
Felipe Alvarez, Jérôme Bolte, Olivier Brahic
math.OCarXiv:1811.10331v12018
A Dynamical Systems Perspective on Nesterov Acceleration
Michael Muehlebach, Michael I. Jordan
math.OCcs.LGcs.SYarXiv:1905.07436v12019
Variance Reduced Value Iteration and Faster Algorithms for Solving Markov Decision Processes
Aaron Sidford, Mengdi Wang, Xian Wu +1
cs.DScs.LGmath.OCarXiv:1710.09988v32017
Theoretical insights into the optimization landscape of over-parameterized shallow neural networks
Mahdi Soltanolkotabi, Adel Javanmard, Jason D. Lee
cs.LGcs.ITmath.OCarXiv:1707.04926v32017
A Progressive Batching L-BFGS Method for Machine Learning
Raghu Bollapragada, Dheevatsa Mudigere, Jorge Nocedal +2
math.OCcs.LGstat.MLarXiv:1802.05374v22018
Fractional Order AGC for Distributed Energy Resources Using Robust Optimization
Indranil Pan, Saptarshi Das
eess.SYcs.AIcs.NEarXiv:1611.09755v12016
Forward-backward envelope for the sum of two nonconvex functions: Further properties and nonmonotone line-search algorithms
Andreas Themelis, Lorenzo Stella, Panagiotis Patrinos
math.OCarXiv:1606.06256v22016
Online Distributed Optimization on Dynamic Networks
Saghar Hosseini, Airlie Chapman, Mehran Mesbahi
math.OCcs.DScs.LGarXiv:1412.7215v12014
Distributed Online Convex Optimization with Time-Varying Coupled Inequality Constraints
Xinlei Yi, Xiuxian Li, Lihua Xie +1
math.OCcs.DCcs.LGarXiv:1903.04277v22019
An Improved Analysis of Stochastic Gradient Descent with Momentum
Yanli Liu, Yuan Gao, Wotao Yin
math.OCarXiv:2007.07989v22020
Rank-Efficient LoRA via Joint Tangent-Space Optimization under Isotropic Curvature
Zihan Zhu, Zhehang Du, Xuyang Chen +5
cs.LGmath.OCstat.MLarXiv:2609.12123v12026
From Linear to Linearizable Optimization: A Novel Framework with Applications to Stationary and Non-stationary DR-submodular Optimization
Mohammad Pedramfar, Vaneet Aggarwal
math.OCcs.CCcs.LGarXiv:2405.00065v42024
Hashing with binary autoencoders
Miguel Á. Carreira-Perpiñán, Ramin Raziperchikolaei
cs.LGcs.CVmath.OCarXiv:1501.00756v12015
To sample or not to sample: Self-triggered control for nonlinear systems
Adolfo Anta, Paulo Tabuada
math.OCmath.DSarXiv:0806.0709v12008
Strongly uncontrollable network topologies
Cesar O. Aguilar
math.OCarXiv:1911.06398v12019
Weak convergence on Douglas-Rachford method
B. F. Svaiter
math.OCmath.FAarXiv:1007.2173v12010
A Unifying Framework for Strong Structural Controllability
Jiajia Jia, Henk J. van Waarde, Harry L. Trentelman +1
math.OCarXiv:1903.03353v12019
Optimal Scheduling of an Isolated Microgrid with Battery Storage Considering Load and Renewable Generation Uncertainties
Yang Li, Zhen Yang, Guoqing Li +2
eess.SPmath.OCarXiv:1808.05691v12018
Provably Efficient Reinforcement Learning with Linear Function Approximation
Chi Jin, Zhuoran Yang, Zhaoran Wang +1
cs.LGmath.OCstat.MLarXiv:1907.05388v22019
Control Barrier Function Based Quadratic Programs for Safety Critical Systems
Aaron D. Ames, Xiangru Xu, Jessy W. Grizzle +1
math.OCeess.SYarXiv:1609.06408v22016
Distributed Constrained Optimization by Consensus-Based Primal-Dual Perturbation Method
Tsung-Hui Chang, Angelia Nedić, Anna Scaglione
eess.SYmath.OCarXiv:1304.5590v22013
Convergence of Adam Under Relaxed Assumptions
Haochuan Li, Alexander Rakhlin, Ali Jadbabaie
math.OCcs.LGstat.MLarXiv:2304.13972v32023
Maximum Hands-Off Control: A Paradigm of Control Effort Minimization
M. Nagahara, D. E. Quevedo, D. Nesic
eess.SYcs.ITmath.OCarXiv:1408.3025v22014
Submodular Combinatorial Information Measures with Applications in Machine Learning
Rishabh Iyer, Ninad Khargonkar, Jeff Bilmes +1
cs.LGcs.DScs.ITarXiv:2006.15412v62020
Learning Mean-Field Games
Xin Guo, Anran Hu, Renyuan Xu +1
math.OCarXiv:1901.09585v42019
Sign-Based Optimizers Are Effective Under Heavy-Tailed Noise
Dingzhi Yu, Hongyi Tao, Yuanyu Wan +2
cs.LGcs.CLmath.OCarXiv:2602.07425v22026
Spectral partitioning for $k$-block averaging kernels of finite Markov chains
Michael C. H. Choi, Youjia Wang
stat.MLcs.ITcs.LGarXiv:2608.21466v12026
Approximation Methods for Bilevel Programming
Saeed Ghadimi, Mengdi Wang
math.OCarXiv:1802.02246v12018
The Best of Many Worlds: Dual Mirror Descent for Online Allocation Problems
Santiago Balseiro, Haihao Lu, Vahab Mirrokni
cs.DScs.LGmath.OCarXiv:2011.10124v32020
Stochastic optimal scheduling of demand response-enabled microgrids with renewable generations: An analytical-heuristic approach
Yang Li, Kang Li, Zhen Yang +3
eess.SYmath.OCarXiv:2111.12322v12021
First Analysis of Local GD on Heterogeneous Data
Ahmed Khaled, Konstantin Mishchenko, Peter Richtárik
cs.LGcs.DCmath.NAarXiv:1909.04715v22019
Convergence results for projected line-search methods on varieties of low-rank matrices via \L{}ojasiewicz inequality
Reinhold Schneider, André Uschmajew
math.OCcs.LGcs.NAarXiv:1402.5284v32014
Meta-Learning with Implicit Gradients
Aravind Rajeswaran, Chelsea Finn, Sham Kakade +1
cs.LGcs.AImath.OCarXiv:1909.04630v12019
Complete Dictionary Recovery over the Sphere II: Recovery by Riemannian Trust-region Method
Ju Sun, Qing Qu, John Wright
cs.ITcs.CVmath.OCarXiv:1511.04777v32015
Stability of Epidemic Models over Directed Graphs: A Positive Systems Approach
Ali Khanafer, Tamer Başar, Bahman Gharesifard
eess.SYcs.SIcs.SYarXiv:1407.6076v22014
Simple algorithms for optimization on Riemannian manifolds with constraints
Changshuo Liu, Nicolas Boumal
math.OCarXiv:1901.10000v22019
Sparse Approximation via Penalty Decomposition Methods
Zhaosong Lu, Yong Zhang
cs.LGmath.OCstat.COarXiv:1205.2334v22012
The numeraire portfolio in semimartingale financial models
Ioannis Karatzas, Constantinos Kardaras
q-fin.PRmath.OCmath.PRarXiv:0803.1877v12008
Towards Understanding Ensemble, Knowledge Distillation and Self-Distillation in Deep Learning
Zeyuan Allen-Zhu, Yuanzhi Li
cs.LGcs.NEmath.OCarXiv:2012.09816v32020

Optimization and Control

Online Placement of Multi-Component Applications in Edge Computing Environments

Global Optimality in Low-rank Matrix Optimization

A Convex Optimization Approach for Finite-Thrust Time-Constrained Cooperative Rendezvous

A survey on high-dimensional Gaussian process modeling with application to Bayesian optimization

Sequence Set Design With Good Correlation Properties via Majorization-Minimization

Learning Model Predictive Control for iterative tasks. A Data-Driven Control Framework

Lions and Muons: Optimization via Stochastic Frank-Wolfe under Heavy-Tailed Noise

Hyperspectral Unmixing Overview: Geometrical, Statistical, and Sparse Regression-Based Approaches

Graduated Non-Convexity for Robust Spatial Perception: From Non-Minimal Solvers to Global Outlier Rejection

New Analysis and Results for the Frank-Wolfe Method

The Augmented Lagrange Multiplier Method for Exact Recovery of Corrupted Low-Rank Matrices

Average-Cost Markov Decision Processes with Weakly Continuous Transition Probabilities

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

Federated Expectation Maximization with heterogeneity mitigation and variance reduction

Distributed Optimal Power Flow Algorithm for Balanced Radial Distribution Networks

On Nonconvex Decentralized Gradient Descent

Distributed Reinforcement Learning for Decentralized Linear Quadratic Control: A Derivative-Free Policy Optimization Approach

Decentralized Deep Learning with Arbitrary Communication Compression

On TD(0) with function approximation: Concentration bounds and a centered variant with exponential convergence

Non-square matrix sensing without spurious local minima via the Burer-Monteiro approach

Combining Prior Knowledge and Data for Robust Controller Design

Hessian Riemannian gradient flows in convex programming

A Dynamical Systems Perspective on Nesterov Acceleration

Variance Reduced Value Iteration and Faster Algorithms for Solving Markov Decision Processes

Theoretical insights into the optimization landscape of over-parameterized shallow neural networks

A Progressive Batching L-BFGS Method for Machine Learning

Fractional Order AGC for Distributed Energy Resources Using Robust Optimization

Forward-backward envelope for the sum of two nonconvex functions: Further properties and nonmonotone line-search algorithms

Online Distributed Optimization on Dynamic Networks

Distributed Online Convex Optimization with Time-Varying Coupled Inequality Constraints

An Improved Analysis of Stochastic Gradient Descent with Momentum

Rank-Efficient LoRA via Joint Tangent-Space Optimization under Isotropic Curvature

From Linear to Linearizable Optimization: A Novel Framework with Applications to Stationary and Non-stationary DR-submodular Optimization

Hashing with binary autoencoders

To sample or not to sample: Self-triggered control for nonlinear systems

Strongly uncontrollable network topologies

Weak convergence on Douglas-Rachford method

A Unifying Framework for Strong Structural Controllability

Optimal Scheduling of an Isolated Microgrid with Battery Storage Considering Load and Renewable Generation Uncertainties

Provably Efficient Reinforcement Learning with Linear Function Approximation

Control Barrier Function Based Quadratic Programs for Safety Critical Systems

Distributed Constrained Optimization by Consensus-Based Primal-Dual Perturbation Method

Convergence of Adam Under Relaxed Assumptions

Maximum Hands-Off Control: A Paradigm of Control Effort Minimization

Submodular Combinatorial Information Measures with Applications in Machine Learning

Learning Mean-Field Games

Sign-Based Optimizers Are Effective Under Heavy-Tailed Noise

Spectral partitioning for $k$-block averaging kernels of finite Markov chains

Approximation Methods for Bilevel Programming

The Best of Many Worlds: Dual Mirror Descent for Online Allocation Problems

Stochastic optimal scheduling of demand response-enabled microgrids with renewable generations: An analytical-heuristic approach

First Analysis of Local GD on Heterogeneous Data

Convergence results for projected line-search methods on varieties of low-rank matrices via \L{}ojasiewicz inequality

Meta-Learning with Implicit Gradients

Complete Dictionary Recovery over the Sphere II: Recovery by Riemannian Trust-region Method

Stability of Epidemic Models over Directed Graphs: A Positive Systems Approach

Simple algorithms for optimization on Riemannian manifolds with constraints

Sparse Approximation via Penalty Decomposition Methods

The numeraire portfolio in semimartingale financial models

Towards Understanding Ensemble, Knowledge Distillation and Self-Distillation in Deep Learning