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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901 to 960 of 1,590

Computational and Statistical Tradeoffs via Convex Relaxation
Venkat Chandrasekaran, Michael I. Jordan
math.STcs.ITmath.OCarXiv:1211.1073v22012
Neural Combinatorial Optimization with Heavy Decoder: Toward Large Scale Generalization
Fu Luo, Xi Lin, Fei Liu +2
cs.LGcs.NEmath.OCarXiv:2310.07985v22023
Off-policy reinforcement learning for $ H_\infty $ control design
Biao Luo, Huai-Ning Wu, Tingwen Huang
eess.SYcs.LGmath.OCarXiv:1311.6107v32013
A proximal iteration for deconvolving Poisson noisy images using sparse representations
François-Xavier Dupé, Jalal Fadili, Jean Luc Starck
stat.APmath.OCmath.STarXiv:0803.2623v22008
diffGrad: An Optimization Method for Convolutional Neural Networks
Shiv Ram Dubey, Soumendu Chakraborty, Swalpa Kumar Roy +3
cs.LGcs.CVcs.NEarXiv:1909.11015v42019
ADD-OPT: Accelerated Distributed Directed Optimization
Chenguang Xi, Ran Xin, Usman A. Khan
math.OCarXiv:1607.04757v32016
Adaptive Gradient Sparsification for Efficient Federated Learning: An Online Learning Approach
Pengchao Han, Shiqiang Wang, Kin K. Leung
cs.LGcs.DCmath.OCarXiv:2001.04756v32020
Forward-Backward Stochastic Neural Networks: Deep Learning of High-dimensional Partial Differential Equations
Maziar Raissi
stat.MLcs.LGeess.SYarXiv:1804.07010v12018
Data-Injection Attacks in Stochastic Control Systems: Detectability and Performance Tradeoffs
Cheng-Zong Bai, Fabio Pasqualetti, Vijay Gupta
math.OCeess.SYarXiv:1704.00748v12017
An optimal randomized incremental gradient method
Guanghui Lan, Yi Zhou
math.OCcs.CCstat.MLarXiv:1507.02000v32015
Cost-Effective Federated Learning Design
Bing Luo, Xiang Li, Shiqiang Wang +2
cs.LGcs.DCcs.NIarXiv:2012.08336v12020
Fast Convergence Rates for Distributed Non-Bayesian Learning
Angelia Nedić, Alex Olshevsky, César A. Uribe
math.OCarXiv:1508.05161v52015
Newton-Type Methods for Non-Convex Optimization Under Inexact Hessian Information
Peng Xu, Fred Roosta, Michael W. Mahoney
math.OCcs.CCcs.LGarXiv:1708.07164v42017
Discrete-Time MDP Modeling for Multi-Item Capacitated Lot Sizing with Stochastic Demand Timing
Léa Bayati, Mohamed Dahmoune, Melek Rodoplu
cs.AIcs.NEmath.OCarXiv:2609.00004v12026
Minibatch vs Local SGD for Heterogeneous Distributed Learning
Blake Woodworth, Kumar Kshitij Patel, Nathan Srebro
cs.LGmath.OCstat.MLarXiv:2006.04735v52020
AC-Feasibility on Tree Networks is NP-Hard
Karsten Lehmann, Alban Grastien, Pascal Van Hentenryck
cs.CCmath.OCarXiv:1410.8253v12014
Golden Ratio Algorithms for Variational Inequalities
Yura Malitsky
math.OCmath.NAarXiv:1803.08832v22018
A Systematic Approach to Mechanism Design with Stochastic Dynamic Stability
Shaya Garjani, Mohammad Shokri, Hamed Kebriaei
eess.SYmath.OCarXiv:2608.29130v12026
Communication-efficient distributed SGD with Sketching
Nikita Ivkin, Daniel Rothchild, Enayat Ullah +3
cs.LGcs.DCmath.OCarXiv:1903.04488v32019
Smoothing proximal gradient method for general structured sparse regression
Xi Chen, Qihang Lin, Seyoung Kim +2
stat.MLcs.LGmath.OCarXiv:1005.4717v42010
Exploring Deep Neural Networks via Layer-Peeled Model: Minority Collapse in Imbalanced Training
Cong Fang, Hangfeng He, Qi Long +1
cs.LGcs.CVmath.OCarXiv:2101.12699v32021
Data-Driven Aerospace Engineering: Reframing the Industry with Machine Learning
Steven L. Brunton, J. Nathan Kutz, Krithika Manohar +9
cs.LGeess.SPmath.OCarXiv:2008.10740v12020
Private Stochastic Convex Optimization: Optimal Rates in Linear Time
Vitaly Feldman, Tomer Koren, Kunal Talwar
cs.LGcs.CRmath.OCarXiv:2005.04763v12020
A Survey of Contextual Optimization Methods for Decision Making under Uncertainty
Utsav Sadana, Abhilash Chenreddy, Erick Delage +3
math.OCcs.LGarXiv:2306.10374v22023
Minimal data rate stabilization of nonlinear systems over networks with large delays
Claudio De Persis
math.OCarXiv:0706.2631v22007
A Corollary for Nonsmooth Systems
N. Fischer, R. Kamalapurkar, W. E. Dixon
math.OCarXiv:1205.6765v22012
Operator-Theoretic Stability and Observer Synthesis for Parameter-Dependent Vlasov--Maxwell Dynamics
Amadou Cissé, Mohamed Boutayeb
eess.SYmath.OCarXiv:2608.28349v12026
A looped-functional approach for robust stability analysis of linear impulsive systems
Corentin Briat, Alexandre Seuret
math.OCeess.SYmath.CAarXiv:1207.1893v12012
Bayesian Optimization with Gradients
Jian Wu, Matthias Poloczek, Andrew Gordon Wilson +1
stat.MLcs.AIcs.LGarXiv:1703.04389v32017
Best practices for comparing optimization algorithms
Vahid Beiranvand, Warren Hare, Yves Lucet
math.OCarXiv:1709.08242v12017
Globally Optimal Energy-Efficient Power Control and Receiver Design in Wireless Networks
Alessio Zappone, Emil Björnson, Luca Sanguinetti +1
math.OCcs.ITarXiv:1602.02923v22016
Enhancing the settling time estimation of a class of fixed-time stable systems
R. Aldana-López, D. Gómez-Gutiérrez, E. Jiménez-Rodríguez +2
math.OCcs.ROeess.SYarXiv:1809.07012v22018
A survey on high-dimensional Gaussian process modeling with application to Bayesian optimization
Mickael Binois, Nathan Wycoff
math.OCarXiv:2111.05040v22021
Optimal Resource Allocation for Network Protection Against Spreading Processes
Victor M. Preciado, Michael Zargham, Chinwendu Enyioha +2
math.OCeess.SYphysics.soc-pharXiv:1309.6270v22013
A Lyapunov Analysis of Momentum Methods in Optimization
Ashia C. Wilson, Benjamin Recht, Michael I. Jordan
math.OCcs.DSarXiv:1611.02635v42016
Multistage Robust Unit Commitment with Dynamic Uncertainty Sets and Energy Storage
Alvaro Lorca, Xu Andy Sun
math.OCarXiv:1604.04890v22016
Semidefinite Representation of Convex Sets
J. William Helton, Jiawang Nie
math.OCmath.AGarXiv:0705.4068v52007
Network Inference via the Time-Varying Graphical Lasso
David Hallac, Youngsuk Park, Stephen Boyd +1
cs.LGcs.SImath.OCarXiv:1703.01958v22017
Dec-BFTRL: Squre-Root Regret for Decentralized Online Upper-Linearizable Optimization under Separation Access with Application to Continuous Submodular Maximization
Yiyang Lu, Mohammad Pedramfar, Vaneet Aggarwal
math.OCcs.AIcs.LGarXiv:2608.30271v12026
Distributed control of reactive power flow in a radial distribution circuit with high photovoltaic penetration
Konstantin Turitsyn, Petr Sulc, Scott Backhaus +1
math.OCarXiv:0912.3281v12009
Stability of Stochastic Gradient Descent on Nonsmooth Convex Losses
Raef Bassily, Vitaly Feldman, Cristóbal Guzmán +1
cs.LGmath.OCstat.MLarXiv:2006.06914v12020
Decision-Focused Learning: Foundations, State of the Art, Benchmark and Future Opportunities
Jayanta Mandi, James Kotary, Senne Berden +4
cs.LGcs.AImath.OCarXiv:2307.13565v42023
How Should a Robot Assess Risk? Towards an Axiomatic Theory of Risk in Robotics
Anirudha Majumdar, Marco Pavone
cs.ROcs.AIeess.SYarXiv:1710.11040v22017
First Order Methods beyond Convexity and Lipschitz Gradient Continuity with Applications to Quadratic Inverse Problems
Jérôme Bolte, Shoham Sabach, Marc Teboulle +1
math.OCmath.NAarXiv:1706.06461v12017
Comparing, Optimising and Benchmarking Quantum Control Algorithms in a Unifying Programming Framework
S. Machnes, U. Sander, S. J. Glaser +4
quant-phmath.OCarXiv:1011.4874v32010
Reinforcement Learning for Integer Programming: Learning to Cut
Yunhao Tang, Shipra Agrawal, Yuri Faenza
cs.LGmath.OCstat.MLarXiv:1906.04859v32019
Derivative-Free Methods for Policy Optimization: Guarantees for Linear Quadratic Systems
Dhruv Malik, Ashwin Pananjady, Kush Bhatia +3
cs.LGmath.OCstat.MLarXiv:1812.08305v32018
Trajectory-Initialized Neural Double Q-Routing for Large-Scale Overhead Hoist Transport Systems
Cheng Gu, Qiusheng Zhao, Anbang Liu +2
cs.LGcs.AImath.OCarXiv:2608.30512v12026
Nearly Minimax Optimal Reinforcement Learning for Linear Mixture Markov Decision Processes
Dongruo Zhou, Quanquan Gu, Csaba Szepesvari
cs.LGmath.OCstat.MLarXiv:2012.08507v22020
AC Power Flow Data in MATPOWER and QCQP Format: iTesla, RTE Snapshots, and PEGASE
Cédric Josz, Stéphane Fliscounakis, Jean Maeght +1
math.OCarXiv:1603.01533v32016
Convergence rates for the RMSprop optimizer with full control of the hyperparameters
Steffen Dereich, Arnulf Jentzen
cs.LGmath.OCmath.PRarXiv:2608.30382v12026
Optimal Power Flow Pursuit
Emiliano Dall'Anese, Andrea Simonetto
math.OCarXiv:1601.07263v42016
The Statistical Complexity of Interactive Decision Making
Dylan J. Foster, Sham M. Kakade, Jian Qian +1
cs.LGmath.OCmath.STarXiv:2112.13487v32021
Gossip consensus algorithms via quantized communication
Ruggero Carli, Fabio Fagnani, Paolo Frasca +1
math.OCeess.SYarXiv:0907.0748v22009
Communication-Efficient Algorithms for Decentralized and Stochastic Optimization
Guanghui Lan, Soomin Lee, Yi Zhou
math.OCcs.LGarXiv:1701.03961v22017
A distributed primal-dual algorithm for computation of generalized Nash equilibria with shared affine coupling constraints via operator splitting methods
Peng Yi, Lacra Pavel
math.OCcs.GTeess.SYarXiv:1703.05388v12017
Bayesian optimization for materials design
Peter I. Frazier, Jialei Wang
stat.MLmath.OCarXiv:1506.01349v12015
Robust stability and stabilization of uncertain linear positive systems via Integral Linear Constraints: L1- and Linfinity-gains characterization
Corentin Briat
eess.SYmath.CAmath.DSarXiv:1204.3554v32012
Optimal load-side control for frequency regulation in smart grids
Enrique Mallada, Changhong Zhao, Steven H. Low
math.OCcs.MAeess.SYarXiv:1410.2931v32014
Improvements to deep convolutional neural networks for LVCSR
Tara N. Sainath, Brian Kingsbury, Abdel-rahman Mohamed +6
cs.LGcs.CLcs.NEarXiv:1309.1501v32013

Optimization and Control

Computational and Statistical Tradeoffs via Convex Relaxation

Neural Combinatorial Optimization with Heavy Decoder: Toward Large Scale Generalization

Off-policy reinforcement learning for $ H_\infty $ control design

A proximal iteration for deconvolving Poisson noisy images using sparse representations

diffGrad: An Optimization Method for Convolutional Neural Networks

ADD-OPT: Accelerated Distributed Directed Optimization

Adaptive Gradient Sparsification for Efficient Federated Learning: An Online Learning Approach

Forward-Backward Stochastic Neural Networks: Deep Learning of High-dimensional Partial Differential Equations

Data-Injection Attacks in Stochastic Control Systems: Detectability and Performance Tradeoffs

An optimal randomized incremental gradient method

Cost-Effective Federated Learning Design

Fast Convergence Rates for Distributed Non-Bayesian Learning

Newton-Type Methods for Non-Convex Optimization Under Inexact Hessian Information

Discrete-Time MDP Modeling for Multi-Item Capacitated Lot Sizing with Stochastic Demand Timing

Minibatch vs Local SGD for Heterogeneous Distributed Learning

AC-Feasibility on Tree Networks is NP-Hard

Golden Ratio Algorithms for Variational Inequalities

A Systematic Approach to Mechanism Design with Stochastic Dynamic Stability

Communication-efficient distributed SGD with Sketching

Smoothing proximal gradient method for general structured sparse regression

Exploring Deep Neural Networks via Layer-Peeled Model: Minority Collapse in Imbalanced Training

Data-Driven Aerospace Engineering: Reframing the Industry with Machine Learning

Private Stochastic Convex Optimization: Optimal Rates in Linear Time

A Survey of Contextual Optimization Methods for Decision Making under Uncertainty

Minimal data rate stabilization of nonlinear systems over networks with large delays

A Corollary for Nonsmooth Systems

Operator-Theoretic Stability and Observer Synthesis for Parameter-Dependent Vlasov--Maxwell Dynamics

A looped-functional approach for robust stability analysis of linear impulsive systems

Bayesian Optimization with Gradients

Best practices for comparing optimization algorithms

Globally Optimal Energy-Efficient Power Control and Receiver Design in Wireless Networks

Enhancing the settling time estimation of a class of fixed-time stable systems

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

Optimal Resource Allocation for Network Protection Against Spreading Processes

A Lyapunov Analysis of Momentum Methods in Optimization

Multistage Robust Unit Commitment with Dynamic Uncertainty Sets and Energy Storage

Semidefinite Representation of Convex Sets

Network Inference via the Time-Varying Graphical Lasso

Dec-BFTRL: Squre-Root Regret for Decentralized Online Upper-Linearizable Optimization under Separation Access with Application to Continuous Submodular Maximization

Distributed control of reactive power flow in a radial distribution circuit with high photovoltaic penetration

Stability of Stochastic Gradient Descent on Nonsmooth Convex Losses

Decision-Focused Learning: Foundations, State of the Art, Benchmark and Future Opportunities

How Should a Robot Assess Risk? Towards an Axiomatic Theory of Risk in Robotics

First Order Methods beyond Convexity and Lipschitz Gradient Continuity with Applications to Quadratic Inverse Problems

Comparing, Optimising and Benchmarking Quantum Control Algorithms in a Unifying Programming Framework

Reinforcement Learning for Integer Programming: Learning to Cut

Derivative-Free Methods for Policy Optimization: Guarantees for Linear Quadratic Systems

Trajectory-Initialized Neural Double Q-Routing for Large-Scale Overhead Hoist Transport Systems

Nearly Minimax Optimal Reinforcement Learning for Linear Mixture Markov Decision Processes

AC Power Flow Data in MATPOWER and QCQP Format: iTesla, RTE Snapshots, and PEGASE

Convergence rates for the RMSprop optimizer with full control of the hyperparameters

Optimal Power Flow Pursuit

The Statistical Complexity of Interactive Decision Making

Gossip consensus algorithms via quantized communication

Communication-Efficient Algorithms for Decentralized and Stochastic Optimization

A distributed primal-dual algorithm for computation of generalized Nash equilibria with shared affine coupling constraints via operator splitting methods

Bayesian optimization for materials design

Robust stability and stabilization of uncertain linear positive systems via Integral Linear Constraints: L1- and Linfinity-gains characterization

Optimal load-side control for frequency regulation in smart grids

Improvements to deep convolutional neural networks for LVCSR