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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1,381 to 1,440 of 1,592

Distributed Robust Power System State Estimation
Vassilis Kekatos, Georgios B. Giannakis
stat.MLmath.OCarXiv:1204.0991v22012
Multiobjective Firefly Algorithm for Continuous Optimization
Xin-She Yang
math.OCarXiv:1303.6336v12013
Sequential Euclidean tree construction with exponential memory: distributional performance and worst-case guarantees
Pedro M. M. de Castro
cs.CGmath.OCarXiv:2608.25298v12026
Nonconvex Optimization Meets Low-Rank Matrix Factorization: An Overview
Yuejie Chi, Yue M. Lu, Yuxin Chen
cs.LGcs.ITeess.SParXiv:1809.09573v32018
On Submodularity and Controllability in Complex Dynamical Networks
Tyler H. Summers, Fabrizio L. Cortesi, John Lygeros
math.OCeess.SYarXiv:1404.7665v32014
FLARE: Verifying MILP Reformulations with LLM-Based Theorem Proving
Henry Robbins, Connor Lawless, Madeleine Udell +1
cs.AIcs.LOmath.OCarXiv:2608.25220v12026
On Convergence of Extended Dynamic Mode Decomposition to the Koopman Operator
Milan Korda, Igor Mezić
math.OCmath.DSmath.SParXiv:1703.04680v42017
An inertial forward-backward algorithm for monotone inclusions
Dirk A. Lorenz, Thomas Pock
cs.CVmath.NAmath.OCarXiv:1403.3522v22014
Combinatorial optimization and reasoning with graph neural networks
Quentin Cappart, Didier Chételat, Elias Khalil +3
cs.LGcs.DScs.NEarXiv:2102.09544v32021
Schrödinger Bridges over Kinetic Swarming Models
Asmaa Eldesoukey, Md Zulfiqur Haider, Italo Napolitano +2
math.OCeess.SYmath-pharXiv:2608.25281v12026
Shampoo: Preconditioned Stochastic Tensor Optimization
Vineet Gupta, Tomer Koren, Yoram Singer
cs.LGmath.OCstat.MLarXiv:1802.09568v22018
Wasserstein Distributionally Robust Optimization: Theory and Applications in Machine Learning
Daniel Kuhn, Peyman Mohajerin Esfahani, Viet Anh Nguyen +1
stat.MLcs.LGmath.OCarXiv:1908.08729v22019
Efficient tensor bases for pairwise comparisons
Konrad Kułakowski, Ryszard Smarzewski
cs.CEecon.EMmath.OCarXiv:2608.25923v12026
Parallelizing the dual revised simplex method
Q. Huangfu, J. A. J. Hall
math.OCmath.NAarXiv:1503.01889v12015
Monte Carlo Gradient Estimation in Machine Learning
Shakir Mohamed, Mihaela Rosca, Michael Figurnov +1
stat.MLcs.LGmath.OCarXiv:1906.10652v22019
Breaking the Hierarchy: Distributed Control & Economic Optimality in Microgrids
Florian Dörfler, John Simpson-Porco, Francesco Bullo
math.OCarXiv:1401.1767v22014
A Stochastic Quasi-Newton Method for Large-Scale Optimization
R. H. Byrd, S. L. Hansen, J. Nocedal +1
math.OCcs.LGstat.MLarXiv:1401.7020v22014
Approximating Energy-Regulation Feasible Region of Virtual Power Plants: A Data-driven Inverse Optimization Approach
Ruike Lyu, Hongye Guo, Qixin Chen
math.OCeess.SYarXiv:2608.25248v12026
Dimensionless Controls of Plasticity Under Alternating Tasks: From Evolutionary Biology to Continual Learning
Owen Skriloff
math.OCcs.LGarXiv:2608.23889v12026
Summaries:한국어
Adaptive Hybrid Subspace Levenberg Marquardt Algorithm with Adequacy Monitor for Large Scale Least Squares Problems
M. Duc Hoang, Timothy J. Lewis
math.NAcs.LGmath.OCarXiv:2608.25524v12026
Scalable Multi-GPU Simulation of 3D Multicellular Growth with RNN-Based Workload Balancing
Matvey Moisseyev, Huijing Du, Dandan Zheng +2
cs.DCcs.CEcs.LGarXiv:2608.25890v12026
The huge Package for High-dimensional Undirected Graph Estimation in R
Tuo Zhao, Han Liu, Kathryn Roeder +2
stat.MLcs.LGmath.OCarXiv:2006.14781v12020
Hyperparameter optimization with approximate gradient
Fabian Pedregosa
stat.MLcs.LGmath.OCarXiv:1602.02355v62016
Chance Constrained Optimal Power Flow: Risk-Aware Network Control under Uncertainty
Daniel Bienstock, Michael Chertkov, Sean Harnett
math.OCeess.SYphysics.soc-pharXiv:1209.5779v22012
Non-convex Optimization for Machine Learning
Prateek Jain, Purushottam Kar
stat.MLcs.LGmath.OCarXiv:1712.07897v12017
Why and When Neural Networks Improve Local Approximation in Optimization
Chengkuo Bian, Pengcheng Xie
cs.LGmath.OCarXiv:2608.24963v12026
On-line Building Energy Optimization using Deep Reinforcement Learning
Elena Mocanu, Decebal Constantin Mocanu, Phuong H. Nguyen +4
cs.LGcs.AImath.OCarXiv:1707.05878v12017
Learning spatially varying regularisation parameters of low regularity for image reconstruction
Kostas Papafitsoros, Luca Calatroni, Andreas Kofler
eess.IVcs.CVmath.OCarXiv:2608.25127v12026
Representing MAX functions using two-hidden-layer ReLU networks
Zhimao Wang, Amitabh Basu
cs.LGmath.OCstat.MLarXiv:2608.25221v12026
A Multi-View Coupled Tensor Decomposition for Lightweight Online Adaptive Traffic Prediction
Quan Yu, Jie Ni, Yu-Hong Dai +1
math.OCcs.LGarXiv:2608.25498v12026
Harmony Search as a Metaheuristic Algorithm
Xin-She Yang
math.OCarXiv:1003.1599v22010
Momentum-Based Variance Reduction in Non-Convex SGD
Ashok Cutkosky, Francesco Orabona
cs.LGmath.OCstat.MLarXiv:1905.10018v32019
Beyond Optimal Rates in Stochastic Optimization: Trajectory-Adaptive Stopping Rules
Liviu Aolaritei, Lucas Lévy, Francis Bach +1
cs.LGmath.OCmath.STarXiv:2608.25551v12026
Asynchronous Decentralized Parallel Stochastic Gradient Descent
Xiangru Lian, Wei Zhang, Ce Zhang +1
math.OCcs.LGstat.MLarXiv:1710.06952v32017
Online Learning: A Modern Introduction Using Convex Optimization
Francesco Orabona
cs.LGmath.OCstat.MLarXiv:1912.13213v102019
Mini-batch Stochastic Approximation Methods for Nonconvex Stochastic Composite Optimization
Saeed Ghadimi, Guanghui Lan, Hongchao Zhang
math.OCarXiv:1308.6594v22013
Cooperative Robot Control and Concurrent Synchronization of Lagrangian Systems
Soon-Jo Chung, Jean-Jacques E. Slotine
math.OCarXiv:0711.1709v42007
Optimal parameter selection for the alternating direction method of multipliers (ADMM): quadratic problems
Euhanna Ghadimi, André Teixeira, Iman Shames +1
math.OCmath.DSarXiv:1306.2454v22013
Spectral partitioning for $k$-block averaging kernels of finite Markov chains
Michael C. H. Choi, Youjia Wang
stat.MLcs.ITcs.LGarXiv:2608.21466v12026
Q-Learning with Stable Infinite-Dimensional Linear Function Approximation
Shengbo Wang
cs.LGmath.OCstat.MLarXiv:2608.22636v12026
NEXT: In-Network Nonconvex Optimization
Paolo Di Lorenzo, Gesualdo Scutari
cs.DCeess.SYmath.OCarXiv:1602.00591v12016
Provably Safe and Robust Learning-Based Model Predictive Control
Anil Aswani, Humberto Gonzalez, S. Shankar Sastry +1
math.OCcs.LGeess.SYarXiv:1107.2487v22011
Convex Relaxation of Optimal Power Flow, Part II: Exactness
Steven H. Low
math.OCeess.SYarXiv:1405.0814v12014
Efficient and Accurate Estimation of Lipschitz Constants for Deep Neural Networks
Mahyar Fazlyab, Alexander Robey, Hamed Hassani +2
cs.LGcs.AImath.OCarXiv:1906.04893v22019
Stochastic gradient descent with initial regularization
Nabil Kahalé
cs.LGmath.OCstat.MLarXiv:2608.22953v12026
Data informativity: a new perspective on data-driven analysis and control
Henk J. van Waarde, Jaap Eising, Harry L. Trentelman +1
math.OCmath.DSarXiv:1908.00468v32019
Optimization-Based Autonomous Racing of 1:43 Scale RC Cars
Alexander Liniger, Alexander Domahidi, Manfred Morari
math.OCcs.ROeess.SYarXiv:1711.07300v12017
Flower Pollination Algorithm: A Novel Approach for Multiobjective Optimization
Xin-She Yang, M. Karamanoglu, X. S. He
math.OCcs.NEnlin.AOarXiv:1408.5332v12014
Low-rank matrix completion by Riemannian optimization---extended version
Bart Vandereycken
math.OCmath.DGmath.NAarXiv:1209.3834v12012
Improving Generalization Performance by Switching from Adam to SGD
Nitish Shirish Keskar, Richard Socher
cs.LGmath.OCarXiv:1712.07628v12017
Non-convex learning via Stochastic Gradient Langevin Dynamics: a nonasymptotic analysis
Maxim Raginsky, Alexander Rakhlin, Matus Telgarsky
cs.LGmath.OCmath.PRarXiv:1702.03849v32017
Communication Efficient Distributed Optimization using an Approximate Newton-type Method
Ohad Shamir, Nathan Srebro, Tong Zhang
cs.LGmath.OCstat.MLarXiv:1312.7853v42013
Model-Free Renewable Scenario Generation Using Generative Adversarial Networks
Yize Chen, Yishen Wang, Daniel Kirschen +1
cs.LGeess.SYmath.OCarXiv:1707.09676v22017
Recent Advances in Bayesian Optimization
Xilu Wang, Yaochu Jin, Sebastian Schmitt +1
cs.LGcs.DCcs.NEarXiv:2206.03301v22022
Network Topology and Communication-Computation Tradeoffs in Decentralized Optimization
Angelia Nedić, Alex Olshevsky, Michael G. Rabbat
math.OCcs.DCcs.MAarXiv:1709.08765v22017
Event-Triggered Communication and Control of Networked Systems for Multi-Agent Consensus
Cameron Nowzari, Eloy Garcia, Jorge Cortes
math.OCarXiv:1712.00429v32017
Optimal rates for zero-order convex optimization: the power of two function evaluations
John C. Duchi, Michael I. Jordan, Martin J. Wainwright +1
math.OCcs.ITstat.MLarXiv:1312.2139v22013
Tight Majorizations and Convergence Rates of Nuclear Norm Minimization IRLS
Christian Kümmerle, Tomas Masak, Dominik Stöger
cs.LGmath.NAmath.OCarXiv:2608.23765v12026
GloptiPoly 3: moments, optimization and semidefinite programming
Didier Henrion, Jean Bernard Lasserre, Johan Lofberg
math.OCarXiv:0709.2559v12007
SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization
Haoming Jiang, Pengcheng He, Weizhu Chen +3
cs.CLcs.LGmath.OCarXiv:1911.03437v52019

Optimization and Control

Distributed Robust Power System State Estimation

Multiobjective Firefly Algorithm for Continuous Optimization

Sequential Euclidean tree construction with exponential memory: distributional performance and worst-case guarantees

Nonconvex Optimization Meets Low-Rank Matrix Factorization: An Overview

On Submodularity and Controllability in Complex Dynamical Networks

FLARE: Verifying MILP Reformulations with LLM-Based Theorem Proving

On Convergence of Extended Dynamic Mode Decomposition to the Koopman Operator

An inertial forward-backward algorithm for monotone inclusions

Combinatorial optimization and reasoning with graph neural networks

Schrödinger Bridges over Kinetic Swarming Models

Shampoo: Preconditioned Stochastic Tensor Optimization

Wasserstein Distributionally Robust Optimization: Theory and Applications in Machine Learning

Efficient tensor bases for pairwise comparisons

Parallelizing the dual revised simplex method

Monte Carlo Gradient Estimation in Machine Learning

Breaking the Hierarchy: Distributed Control & Economic Optimality in Microgrids

A Stochastic Quasi-Newton Method for Large-Scale Optimization

Approximating Energy-Regulation Feasible Region of Virtual Power Plants: A Data-driven Inverse Optimization Approach

Dimensionless Controls of Plasticity Under Alternating Tasks: From Evolutionary Biology to Continual Learning

Adaptive Hybrid Subspace Levenberg Marquardt Algorithm with Adequacy Monitor for Large Scale Least Squares Problems

Scalable Multi-GPU Simulation of 3D Multicellular Growth with RNN-Based Workload Balancing

The huge Package for High-dimensional Undirected Graph Estimation in R

Hyperparameter optimization with approximate gradient

Chance Constrained Optimal Power Flow: Risk-Aware Network Control under Uncertainty

Non-convex Optimization for Machine Learning

Why and When Neural Networks Improve Local Approximation in Optimization

On-line Building Energy Optimization using Deep Reinforcement Learning

Learning spatially varying regularisation parameters of low regularity for image reconstruction

Representing MAX functions using two-hidden-layer ReLU networks

A Multi-View Coupled Tensor Decomposition for Lightweight Online Adaptive Traffic Prediction

Harmony Search as a Metaheuristic Algorithm

Momentum-Based Variance Reduction in Non-Convex SGD

Beyond Optimal Rates in Stochastic Optimization: Trajectory-Adaptive Stopping Rules

Asynchronous Decentralized Parallel Stochastic Gradient Descent

Online Learning: A Modern Introduction Using Convex Optimization

Mini-batch Stochastic Approximation Methods for Nonconvex Stochastic Composite Optimization

Cooperative Robot Control and Concurrent Synchronization of Lagrangian Systems

Optimal parameter selection for the alternating direction method of multipliers (ADMM): quadratic problems

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

Q-Learning with Stable Infinite-Dimensional Linear Function Approximation

NEXT: In-Network Nonconvex Optimization

Provably Safe and Robust Learning-Based Model Predictive Control

Convex Relaxation of Optimal Power Flow, Part II: Exactness

Efficient and Accurate Estimation of Lipschitz Constants for Deep Neural Networks

Stochastic gradient descent with initial regularization

Data informativity: a new perspective on data-driven analysis and control

Optimization-Based Autonomous Racing of 1:43 Scale RC Cars

Flower Pollination Algorithm: A Novel Approach for Multiobjective Optimization

Low-rank matrix completion by Riemannian optimization---extended version

Improving Generalization Performance by Switching from Adam to SGD

Non-convex learning via Stochastic Gradient Langevin Dynamics: a nonasymptotic analysis

Communication Efficient Distributed Optimization using an Approximate Newton-type Method

Model-Free Renewable Scenario Generation Using Generative Adversarial Networks

Recent Advances in Bayesian Optimization

Network Topology and Communication-Computation Tradeoffs in Decentralized Optimization

Event-Triggered Communication and Control of Networked Systems for Multi-Agent Consensus

Optimal rates for zero-order convex optimization: the power of two function evaluations

Tight Majorizations and Convergence Rates of Nuclear Norm Minimization IRLS

GloptiPoly 3: moments, optimization and semidefinite programming

SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization