Distributed Optimization

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Overview

Distributed optimization studies how multiple machines, clients, or robots can solve a shared problem using local data and limited communication. Common approaches include consensus and decentralized gradient methods, local or federated SGD, ADMM and primal-dual algorithms, and asynchronous updates; communication can be reduced through compression, quantization, or less frequent synchronization. These methods support settings from large-model training and statistical learning to robot coordination, energy systems, and networked control. A central challenge is balancing communication and computation against convergence when data and worker speeds differ, messages are delayed, or participants may be unreliable or adversarial.

Latest papers

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92 papers11 papers in the last four weeks, up 267% on the four weeks before. 0.1% of all new papers.

  1. Parallel AI Agent Collaboration as Graph-Structured Distributed Block Optimization

    Oct 21, 2026Hanmin Li, Yury Demidovich, Peter RichtárikMulti-Agent CollaborationMulti-Agent System Optimization

    King Abdullah University of Science and Technology Thuwal, Saudi Arabia

  2. On Johnson-Lindenstrauss Transforms for Byzantine-Robust Optimization

    Oct 20, 2026Aleksandr Shestakov, Vladimir Aletov, Aleksandr BeznosikovRobust OptimizationDistributed Optimization

    Basic Research of Artificial Intelligence Laboratory · MBZUAI · Federated Learning Problems Laboratory

  3. Low-Bit Distributed Constrained Optimization with Application to Optimal Scheduling and Allocation

    Oct 17, 2026Mohammadreza Doostmohammadian, Sergio PequitoDistributed OptimizationConstrained Optimization

  4. Adding Heavy-Ball Momentum to Distributed Constrained Optimization for Energy Resource Management Subject to Time-Delays and Quantization

    Oct 17, 2026Mohammadreza Doostmohammadian, Sergio PequitoDistributed OptimizationConstrained Optimization

  5. Beyond Aggregate Drift: Optimal Client-Specific Windows in Federated Learning

    Oct 11, 2026Yuriy Dorn, Dmitrii Vishovan, Kirill Novoselov +3Federated LearningOnline Federated Learning

    Lomonosov Moscow State University · Innopolis University · Moscow Independent Research Institute of Artificial Intelligence +3

  6. Data-Topology Compatibility Enables Personalization in Decentralized Learning

    Oct 10, 2026Veronica Xu, Lingfei Wang, Chenlei Leng +1Decentralized LearningDistributed Optimization

  7. Scalar Communication via Random Direction Refreshing for Distributed Optimization

    Oct 5, 2026Mohammadreza Rostami, Solmaz S. KiaDistributed OptimizationDecentralized Optimization

    Department of Mechanical and Aerospace Engineering, University of California Irvine, Irvine, CA 92697

  8. Distributed Algorithms for αα-Potential Functions in General-Sum Games

    Oct 4, 2026Yifei Chen, Chinmay MaheshwariDistributed OptimizationPotential Games

    Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, Maryland, USA · Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, Maryland, USA

  9. Population Scaling or Data Dilution? Dynamics of Local Topology Evolution in Decentralized Learning

    Oct 4, 2026Yin-Kuan Liang, Yan Gao, Yang LongDistributed OptimizationDecentralized Learning

    Durham University · University of Cambridge

  10. Robustifying Asynchronous SGD via Soft Throttling

    Sep 30, 2026Kaoru Otsuka, Maxime Meyer, Yuki Takezawa +2Distributed OptimizationFault-Tolerant Distributed Training

    Okinawa Institute of Science and Technology · National University of Singapore · Toyota Motor Corporation +1

  11. MegaGraph: Towards Efficient Training of Large-Scale Graph Transformers with Automated Hybrid Parallelism

    Sep 28, 2026Tong Qiao, Ao Zhou, Yingjie Qi +2Distributed OptimizationHigh-Performance Computing

    School of Computer Science and Engineering, Beihang University, China · School of Software, Beihang University, China · State Key Laboratory of Complex and Critical Software Environment, Beihang University, China +1

  12. Resource-Efficient Distributed Recursive Gaussian Processes

    Sep 22, 2026Josephine King, Ali Emre Balci, Raj Thilak RajanDistributed OptimizationGaussian Processes

    Signal Processing Systems, Faculty of EEMCS, Delft University of Technology, Mekelweg 4, 2628CD, Delft, The Netherlands

  13. Revisiting Distributed Sign-Based Variance Reduction

    Sep 16, 2026Wei Jiang, Zechao Li, Lijun ZhangSign-Based OptimizationCommunication-Efficient Distributed Training

    School of Computer Science and Engineering, Nanjing University of Science and Technology, China · National Key Laboratory for Novel Software Technology,Nanjing University, China · School of Artificial Intelligence, Nanjing University, China

  14. Bridging the Gap Between Homogeneous and Heterogeneous Asynchronous Optimization Is Surprisingly Difficult

    Sep 15, 2026Alexander TyurinDistributed OptimizationStochastic Optimization Convergence

    AXXX, Moscow, Russia · Applied AI Institute, Moscow, Russia

  15. Fully Distributed GNE Algorithms for Multi-Robot Placement without Consensus on Multipliers

    Aug 29, 2026Shao-An Yin, Mingyi Hong, Nicola EliaNash Equilibrium ComputationDistributed Optimization

    Department of Electrical and Computer Engineering, University of Minnesota, USA

  16. Distributed Training using an Intelligent Network

    Aug 26, 2026Nihar Shah, Ben BlierDistributed TrainingCommunication-Efficient Distributed Training

    DoubleZero Foundation

  17. SSTQ:Privacy-Preserving Vector Quantization via Subsampled Stochastic TurboQuant

    Aug 5, 2026Adel Javanmard, David P. Woodruff, Vahab MirrokniDistributed OptimizationVector Quantization

    University of Southern California · Google Research · Carnegie Mellon University

  18. A Spectral Filtering Approach to Regret Analysis of Distributed Online Control for Linear Dynamical Systems

    Aug 3, 2026Ting-Jui ChangDynamical SystemsDistributed Optimization

    T.J. Chang is with the Department of Aeronautics and Astronautics, National Cheng Kung University, Taiwan.

  19. Using Non-Lipschitz Signum-based Functions for Distributed Optimization and Machine Learning: Trade-off Between Con-vergence Rate and Optimality Gap

    Aug 2, 2026Mohammadreza Doostmohammadian, Amir Ahmad Ghods, Alireza Aghasi +2Sign-Based OptimizationDistributed Optimization

    Faculty of Mechanical Engineering, Semnan University, Semnan, Iran · Department of Electrical Engineering and Computer Science, Oregon State University, Oregon, USA · Institute of Computational Mathematics and Information Technologies, Kazan Federal University, Russia +1

  20. Data-Driven Pinball-Loss Selection for Vertically Distributed Elastic-Net SVMs

    Aug 2, 2026Xiaofei Wu, Kai Qi, Rongmei LiangDistributed OptimizationAdaptive Loss Weighting

    Yunnan Key Laboratory of Statistical Modeling and Data Analysis, School of Mathematics and Statistics, Yunnan University, East Outer Ring South Road, University Town, Chenggong District, Kunming, Yunnan, China · National Center for Applied Mathematics in Chongqing, Chongqing Normal University, No. 37 University Town Middle Road, Shapingba District, Chongqing, China · Department of Statistics and Data Science, Southern University of Science and Technology, 1088 Xueyuan Avenue, Nanshan District, Shenzhen, Guangdong 518055, China

  21. First-order Constrained Trilevel Optimization Over Distributed Networks for Robust Coreset Selection

    Jul 30, 2026Yang Jiao, Kaixuan Jiao, Kai Yang +4Distributed OptimizationRobust Optimization

    Richard · Southeast University · Anhui University +3

  22. Distributed Constraint Optimization via Online Learning and Iterative Pricing with Application to Large-Scale Satellite Scheduling

    Jul 28, 2026Itai Zilberstein, Pranav Rajbhandari, Steve Chien +1Distributed OptimizationPotential Games

    Department of Computer Science, Carnegie Mellon University · Jet Propulsion Laboratory, California Institute of Technology · Additional affiliations: Strategy Robot, Inc., Strategic Machine, Inc., Optimized Markets, Inc.

  23. Distributed Model-Based Diffusion For Scalable Multi-Robot Trajectory Optimization

    Jul 23, 2026Haejoon Lee, Xinyi Wang, Taekyung Kim +1Multi-Robot Motion PlanningDistributed Optimization

    Robotics Department, University of Michigan, Ann Arbor, MI, USA

  24. DQAOA-GPT: AI-Accelerated Distributed Quantum Optimization for Combinatorial Problems

    Jul 22, 2026Seongmin Kim, Abhinav Rijal, Yuri Alexeev +5Distributed OptimizationCombinatorial Optimization

    National Center for Computational Sciences, Oak Ridge National Laboratory, Oak Ridge, TN, USA · Department of Physics & Astronomy, University of Tennessee, Knoxville, TN, USA · NVIDIA Corporation, Santa Clara, CA, USA +3

  25. Decentralized Gradient Descent: Bottleneck Regimes and Budget Complexity

    Jul 13, 2026Nicolò MichelusiDistributed OptimizationStochastic Optimization Convergence

    School of Electrical, Computer and Energy Engineering, Arizona State University.

  26. Can Model Merging Improve Aggregation in DiLoCo?

    Jul 3, 2026Stefan Horoi, Benjamin Thérien, Guy Wolf +1Communication-Efficient Distributed TrainingDistributed Optimization

    Université de Montréal · Mila – Quebec AI Institute · Concordia University

  27. Technical Report: Asynchronous Distributed Trajectory Estimation of Multi-Robot Systems

    Jul 1, 2026Adam Pooley, Matthew HaleMulti-Robot SystemsDistributed Optimization

    School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA

  28. Distributed Online Bandit Submodular Maximization with Bounded Sampling Violations

    Jul 1, 2026Bin Du, Chang Liu, Dingqi Zhu +2Submodular OptimizationDistributed Optimization

    College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China · School of Artificial Intelligence and Automation at the Huazhong University of Science and Technology, Wuhan, China · School of Aeronautics and Astronautics, Purdue University, West Lafayette, IN 47906, USA

  29. Second-Order KKT Guarantees for Bregman ADMM in Nonconvex and Non-Lipschitz Optimization

    Jun 26, 2026Shuang Li, Zhihui Zhu, Qiuwei LiOptimization Convergence AnalysisDistributed Optimization

    Department of Electrical and Computer Engineering, Iowa State University, Ames, Iowa 50014, USA · Department of Computer Science and Engineering, Ohio State University, Columbus, Ohio 43210, USA · DAMO Academy, Alibaba Group US, Bellevue, Washington 98004, USA

  30. DMuon: Efficient Distributed Muon Training with Near-Adam Overhead

    Jun 25, 2026Vincent Chen, Starrick Liu, Regis Cheng +8Deep Learning OptimizationDistributed Optimization

    X SQUARE ROBOT TEAM