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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1,681 to 1,740 of 2,617

Black Box Submodular Maximization: Discrete and Continuous Settings
Lin Chen, Mingrui Zhang, Hamed Hassani +1
cs.LGcs.DSmath.OCarXiv:1901.09515v22019
A Generic First-Order Algorithmic Framework for Bi-Level Programming Beyond Lower-Level Singleton
Risheng Liu, Pan Mu, Xiaoming Yuan +2
cs.LGcs.CVmath.DSarXiv:2006.04045v22020
SGD: General Analysis and Improved Rates
Robert Mansel Gower, Nicolas Loizou, Xun Qian +3
cs.LGmath.OCstat.MLarXiv:1901.09401v42019
Distributed event-triggered coordination for average consensus on weight-balanced digraphs
Cameron Nowzari, Jorge Cortes
math.OCarXiv:1407.7921v32014
Markov-Nash Equilibria in Mean-Field Games with Discounted Cost
Naci Saldi, Tamer Başar, Maxim Raginsky
eess.SYcs.SYmath.OCarXiv:1612.07878v22016
On the Convergence of Model Free Learning in Mean Field Games
Romuald Elie, Julien Pérolat, Mathieu Laurière +2
math.OCcs.LGstat.MLarXiv:1907.02633v32019
Bi-Level Volt-VAR Optimization to Coordinate Smart Inverters with Voltage Control Devices
Rahul Ranjan Jha, Anamika Dubey, Chen-Ching Liu +1
math.OCarXiv:1912.03596v12019
Decentralized Optimal Dispatch of Photovoltaic Inverters in Residential Distribution Systems
Emiliano Dall'Anese, Sairaj V. Dhople, Brian B. Johnson +1
math.OCarXiv:1403.1341v22014
Graph Matching: Relax at Your Own Risk
Vince Lyzinski, Donniell Fishkind, Marcelo Fiori +3
stat.MLmath.OCarXiv:1405.3133v32014
Gradient Descent Finds Global Minima of Deep Neural Networks
Simon S. Du, Jason D. Lee, Haochuan Li +2
cs.LGcs.AIcs.CVarXiv:1811.03804v42018
A proximal difference-of-convex algorithm with extrapolation
Bo Wen, Xiaojun Chen, Ting Kei Pong
math.OCarXiv:1612.06265v22016
On Distributionally Robust Chance Constrained Programs with Wasserstein Distance
Weijun Xie
math.OCarXiv:1806.07418v42018
Deep Reinforcement Learning for Solving the Heterogeneous Capacitated Vehicle Routing Problem
Jingwen Li, Yining Ma, Ruize Gao +4
cs.LGmath.OCarXiv:2110.02629v22021
On the Convergence of Adaptive Gradient Methods for Nonconvex Optimization
Dongruo Zhou, Jinghui Chen, Yuan Cao +2
cs.LGmath.OCstat.MLarXiv:1808.05671v42018
Convergence of trust-region methods based on probabilistic models
Afonso S. Bandeira, Katya Scheinberg, Luis Nunes Vicente
math.OCmath.PRarXiv:1304.2808v12013
Relative Lipschitzness in Extragradient Methods and a Direct Recipe for Acceleration
Michael B. Cohen, Aaron Sidford, Kevin Tian
math.OCcs.DScs.LGarXiv:2011.06572v22020
Stochastic Variance Reduction for Nonconvex Optimization
Sashank J. Reddi, Ahmed Hefny, Suvrit Sra +2
math.OCcs.LGcs.NEarXiv:1603.06160v22016
Optimization-Based Collision Avoidance
Xiaojing Zhang, Alexander Liniger, Francesco Borrelli
math.OCcs.ROeess.SYarXiv:1711.03449v32017
DSOS and SDSOS Optimization: More Tractable Alternatives to Sum of Squares and Semidefinite Optimization
Amir Ali Ahmadi, Anirudha Majumdar
math.OCcs.DSeess.SYarXiv:1706.02586v32017
Secure and Privacy-Preserving Consensus
Minghao Ruan, Huan Gao, Yongqiang Wang
math.OCcs.CRarXiv:1707.04491v42017
Stochastic Frank-Wolfe Methods for Nonconvex Optimization
Sashank J. Reddi, Suvrit Sra, Barnabas Poczos +1
math.OCcs.LGstat.MLarXiv:1607.08254v22016
Neural networks for spectral optimization
Alexis de Villeroché, Beniamin Bogosel, Stéphane Breuils +2
cs.LGcs.AImath.OCarXiv:2609.36047v12026
Scalable Semidefinite Programming
Alp Yurtsever, Joel A. Tropp, Olivier Fercoq +2
math.OCmath.COarXiv:1912.02949v22019
Multi-Robot Control Using Time-Varying Density Functions
Sung G. Lee, Magnus Egerstedt
math.OCcs.ROarXiv:1404.0338v12014
Funnel Libraries for Real-Time Robust Feedback Motion Planning
Anirudha Majumdar, Russ Tedrake
cs.ROcs.AIeess.SYarXiv:1601.04037v32016
Towards Theoretically Understanding Why SGD Generalizes Better Than ADAM in Deep Learning
Pan Zhou, Jiashi Feng, Chao Ma +3
cs.LGcs.AImath.OCarXiv:2010.05627v22020
Linear Contextual Bandits with Knapsacks
Shipra Agrawal, Nikhil R. Devanur
cs.LGmath.OCstat.MLarXiv:1507.06738v22015
A Linearly-Convergent Stochastic L-BFGS Algorithm
Philipp Moritz, Robert Nishihara, Michael I. Jordan
math.OCcs.LGmath.NAarXiv:1508.02087v22015
Encrypted control for networked systems -- An illustrative introduction and current challenges
M. Schulze Darup, A. B. Alexandru, D. E. Quevedo +1
eess.SYcs.CRcs.SYarXiv:2010.00268v12020
Oracle Complexity of Stochastic Fixed-Point Equations with Nonexpansive Maps
Jelena Diakonikolas, Cristóbal Guzmán, David Martínez-Rubio
math.OCcs.DScs.LGarXiv:2609.09524v12026
signSGD: Compressed Optimisation for Non-Convex Problems
Jeremy Bernstein, Yu-Xiang Wang, Kamyar Azizzadenesheli +1
cs.LGcs.DCmath.OCarXiv:1802.04434v32018
You Only Propagate Once: Accelerating Adversarial Training via Maximal Principle
Dinghuai Zhang, Tianyuan Zhang, Yiping Lu +2
stat.MLcs.LGmath.OCarXiv:1905.00877v62019
Convex Relaxation of Optimal Power Flow, Part I: Formulations and Equivalence
Steven H. Low
math.OCeess.SYarXiv:1405.0766v12014
Fictitious Play for Mean Field Games: Continuous Time Analysis and Applications
Sarah Perrin, Julien Perolat, Mathieu Laurière +3
math.OCcs.AIarXiv:2007.03458v22020
Advances in Continuous-Time Multiparametric Optimal Control: The Role of Time-Varying Active Constraints
Lida Lamakani, Efstratios N. Pistikopoulos
math.OCcs.SYeess.SYarXiv:2610.02680v12026
A Variational Perspective on Accelerated Methods in Optimization
Andre Wibisono, Ashia C. Wilson, Michael I. Jordan
math.OCcs.LGstat.MLarXiv:1603.04245v12016
The Limit Points of (Optimistic) Gradient Descent in Min-Max Optimization
Constantinos Daskalakis, Ioannis Panageas
math.OCcs.LGstat.MLarXiv:1807.03907v22018
Asynchronous Stochastic Coordinate Descent: Parallelism and Convergence Properties
Ji Liu, Stephen J. Wright
math.OCarXiv:1403.3862v22014
Accelerating Stochastic Composition Optimization
Mengdi Wang, Ji Liu, Ethan X. Fang
math.OCstat.MLarXiv:1607.07329v12016
Neural Policy Gradient Methods: Global Optimality and Rates of Convergence
Lingxiao Wang, Qi Cai, Zhuoran Yang +1
cs.LGmath.OCstat.MLarXiv:1909.01150v32019
Multiobjective Firefly Algorithm for Continuous Optimization
Xin-She Yang
math.OCarXiv:1303.6336v12013
Distributed strategies for generating weight-balanced and doubly stochastic digraphs
Bahman Gharesifard, Jorge Cortes
math.OCeess.SYarXiv:0911.0232v62009
The rate of convergence of Nesterov's accelerated forward-backward method is actually faster than $1/k^{2}$
Hedy Attouch, Juan Peypouquet
math.OCarXiv:1510.08740v42015
Secure estimation and control for cyber-physical systems under adversarial attacks
Hamza Fawzi, Paulo Tabuada, Suhas Diggavi
math.OCcs.CRcs.ITarXiv:1205.5073v12012
Iteration Complexity of Randomized Block-Coordinate Descent Methods for Minimizing a Composite Function
Peter Richtárik, Martin Takáč
math.OCstat.MLarXiv:1107.2848v12011
Directional convergence and alignment in deep learning
Ziwei Ji, Matus Telgarsky
cs.LGcs.NEmath.OCarXiv:2006.06657v22020
Network Inference via the Time-Varying Graphical Lasso
David Hallac, Youngsuk Park, Stephen Boyd +1
cs.LGcs.SImath.OCarXiv:1703.01958v22017
Controllability transition and nonlocality in network control
Jie Sun, Adilson E. Motter
cond-mat.dis-nnmath.OCnlin.AOarXiv:1305.5848v12013
Projection Operator in Adaptive Systems
Eugene Lavretsky, Travis E. Gibson
nlin.AOcs.SYeess.SYarXiv:1112.4232v62011
Fast Catch-Up, Late Switching: Optimal Batch Size Scheduling via Functional Scaling Laws
Jinbo Wang, Binghui Li, Zhanpeng Zhou +5
cs.LGmath.OCstat.MLarXiv:2602.14208v22026
Incentivizing Energy Trading for Interconnected Microgrids
Hao Wang, Jianwei Huang
cs.GTmath.OCarXiv:1609.07576v12016
Global Deterministic Optimization with Artificial Neural Networks Embedded
Artur M Schweidtmann, Alexander Mitsos
math.OCarXiv:1801.07114v22018
GPU-Enabled Large-Scale Optimization Using Randomized Linear Algebra
Pratik Rathore, Zachary Frangella, Parth Nobel +2
cs.LGmath.OCstat.MLarXiv:2609.08136v12026
MADMM: a generic algorithm for non-smooth optimization on manifolds
Artiom Kovnatsky, Klaus Glashoff, Michael M. Bronstein
math.OCmath.NAarXiv:1505.07676v12015
Differentially Private Distributed Convex Optimization via Functional Perturbation
Erfan Nozari, Pavankumar Tallapragada, Jorge Cortés
math.OCmath.DSarXiv:1512.00369v32015
Stochastic gradient descent performs variational inference, converges to limit cycles for deep networks
Pratik Chaudhari, Stefano Soatto
cs.LGcond-mat.stat-mechmath.OCarXiv:1710.11029v22017
Linear Quadratic Stochastic Differential Games: Open-Loop and Closed-Loop Saddle Points
Jingrui Sun, Jiongmin Yong
math.OCarXiv:1401.4754v12014
Stochastic Optimization with Heavy-Tailed Noise via Accelerated Gradient Clipping
Eduard Gorbunov, Marina Danilova, Alexander Gasnikov
math.OCcs.LGarXiv:2005.10785v22020
BoTorch: A Framework for Efficient Monte-Carlo Bayesian Optimization
Maximilian Balandat, Brian Karrer, Daniel R. Jiang +4
cs.LGcs.DCmath.OCarXiv:1910.06403v32019
Gradient Descent Can Take Exponential Time to Escape Saddle Points
Simon S. Du, Chi Jin, Jason D. Lee +3
math.OCcs.LGstat.MLarXiv:1705.10412v22017

Optimization and Control

Black Box Submodular Maximization: Discrete and Continuous Settings

A Generic First-Order Algorithmic Framework for Bi-Level Programming Beyond Lower-Level Singleton

SGD: General Analysis and Improved Rates

Distributed event-triggered coordination for average consensus on weight-balanced digraphs

Markov-Nash Equilibria in Mean-Field Games with Discounted Cost

On the Convergence of Model Free Learning in Mean Field Games

Bi-Level Volt-VAR Optimization to Coordinate Smart Inverters with Voltage Control Devices

Decentralized Optimal Dispatch of Photovoltaic Inverters in Residential Distribution Systems

Graph Matching: Relax at Your Own Risk

Gradient Descent Finds Global Minima of Deep Neural Networks

A proximal difference-of-convex algorithm with extrapolation

On Distributionally Robust Chance Constrained Programs with Wasserstein Distance

Deep Reinforcement Learning for Solving the Heterogeneous Capacitated Vehicle Routing Problem

On the Convergence of Adaptive Gradient Methods for Nonconvex Optimization

Convergence of trust-region methods based on probabilistic models

Relative Lipschitzness in Extragradient Methods and a Direct Recipe for Acceleration

Stochastic Variance Reduction for Nonconvex Optimization

Optimization-Based Collision Avoidance

DSOS and SDSOS Optimization: More Tractable Alternatives to Sum of Squares and Semidefinite Optimization

Secure and Privacy-Preserving Consensus

Stochastic Frank-Wolfe Methods for Nonconvex Optimization

Neural networks for spectral optimization

Scalable Semidefinite Programming

Multi-Robot Control Using Time-Varying Density Functions

Funnel Libraries for Real-Time Robust Feedback Motion Planning

Towards Theoretically Understanding Why SGD Generalizes Better Than ADAM in Deep Learning

Linear Contextual Bandits with Knapsacks

A Linearly-Convergent Stochastic L-BFGS Algorithm

Encrypted control for networked systems -- An illustrative introduction and current challenges

Oracle Complexity of Stochastic Fixed-Point Equations with Nonexpansive Maps

signSGD: Compressed Optimisation for Non-Convex Problems

You Only Propagate Once: Accelerating Adversarial Training via Maximal Principle

Convex Relaxation of Optimal Power Flow, Part I: Formulations and Equivalence

Fictitious Play for Mean Field Games: Continuous Time Analysis and Applications

Advances in Continuous-Time Multiparametric Optimal Control: The Role of Time-Varying Active Constraints

A Variational Perspective on Accelerated Methods in Optimization

The Limit Points of (Optimistic) Gradient Descent in Min-Max Optimization

Asynchronous Stochastic Coordinate Descent: Parallelism and Convergence Properties

Accelerating Stochastic Composition Optimization

Neural Policy Gradient Methods: Global Optimality and Rates of Convergence

Multiobjective Firefly Algorithm for Continuous Optimization

Distributed strategies for generating weight-balanced and doubly stochastic digraphs

The rate of convergence of Nesterov's accelerated forward-backward method is actually faster than $1/k^{2}$

Secure estimation and control for cyber-physical systems under adversarial attacks

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

Directional convergence and alignment in deep learning

Network Inference via the Time-Varying Graphical Lasso

Controllability transition and nonlocality in network control

Projection Operator in Adaptive Systems

Fast Catch-Up, Late Switching: Optimal Batch Size Scheduling via Functional Scaling Laws

Incentivizing Energy Trading for Interconnected Microgrids

Global Deterministic Optimization with Artificial Neural Networks Embedded

GPU-Enabled Large-Scale Optimization Using Randomized Linear Algebra

MADMM: a generic algorithm for non-smooth optimization on manifolds

Differentially Private Distributed Convex Optimization via Functional Perturbation

Stochastic gradient descent performs variational inference, converges to limit cycles for deep networks

Linear Quadratic Stochastic Differential Games: Open-Loop and Closed-Loop Saddle Points

Stochastic Optimization with Heavy-Tailed Noise via Accelerated Gradient Clipping

BoTorch: A Framework for Efficient Monte-Carlo Bayesian Optimization

Gradient Descent Can Take Exponential Time to Escape Saddle Points