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Distributed Optimization

The goal of Distributed Optimization is to optimize a certain objective defined over millions of billions of data that is distributed over many machines by utilizing the computational power of these machines.

Source: Analysis of Distributed StochasticDual Coordinate Ascent

Papers

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Showing 1–50 of 536 papers

TitleStatusHype
Communication Efficient, Differentially Private Distributed Optimization using Correlation-Aware Sketching—0
DPLib: A Standard Benchmark Library for Distributed Power System Analysis and OptimizationCode1
Multi-Timescale Gradient Sliding for Distributed Optimization—0
Decentralized Optimization on Compact Submanifolds by Quantized Riemannian Gradient Tracking—0
Distributed gradient methods under heavy-tailed communication noise—0
Online distributed optimization for spatio-temporally constrained real-time peer-to-peer energy trading—0
Privacy-Preserving Peer-to-Peer Energy Trading via Hybrid Secure Computations—0
Federated Learning: From Theory to Practice—0
Beyond Self-Repellent Kernels: History-Driven Target Towards Efficient Nonlinear MCMC on General Graphs—0
LAGO: Few-shot Crosslingual Embedding Inversion Attacks via Language Similarity-Aware Graph Optimization—0
Distributed Optimization with Efficient Communication, Event-Triggered Solution Enhancement, and Operation Stopping—0
Distributed model predictive control without terminal cost under inexact distributed optimization—0
Hessian Riemannian Flow For Multi-Population Wardrop Equilibrium—0
Residual-Evasive Attacks on ADMM in Distributed Optimization—0
Distributed Optimization with Gradient Tracking over Heterogeneous Delay-Prone Directed Networks—0
Graph Neural Network-Based Distributed Optimal Control for Linear Networked Systems: An Online Distributed Training Approach—0
Reducing the Communication of Distributed Model Predictive Control: Autoencoders and Formation Control—0
Dynamic Incentive Strategies for Smart EV Charging Stations: An LLM-Driven User Digital Twin Approach—0
Combining Graph Attention Networks and Distributed Optimization for Multi-Robot Mixed-Integer Convex Programming—0
ALADIN-β: A Distributed Optimization Algorithm for Solving MPCC Problems—0
Convergence Theory of Flexible ALADIN for Distributed Optimization—0
Collaborative Satisfaction of Long-Term Spatial Constraints in Multi-Agent Systems: A Distributed Optimization Approach (extended version)—0
Communication Efficient Federated Learning with Linear Convergence on Heterogeneous Data—0
Byzantine-Resilient Federated Learning via Distributed Optimization—0
Accelerated Distributed Optimization with Compression and Error Feedback—0
Distributed Pose Graph Optimization using the Splitting Method based on the Alternating Direction Method of Multipliers—0
From Centralized to Decentralized Federated Learning: Theoretical Insights, Privacy Preservation, and Robustness Challenges—0
Opportunistic Routing in Wireless Communications via Learnable State-Augmented PoliciesCode0
Unbiased and Sign Compression in Distributed Learning: Comparing Noise Resilience via SDEs—0
Smoothed Normalization for Efficient Distributed Private Optimization—0
Fundamental Bias in Inverting Random Sampling Matrices with Application to Sub-sampled Newton—0
Sign Operator for Coping with Heavy-Tailed Noise in Non-Convex Optimization: High Probability Bounds Under (L_0, L_1)-Smoothness—0
Efficient Distributed Optimization under Heavy-Tailed Noise—0
A Survey of Optimization Methods for Training DL Models: Theoretical Perspective on Convergence and Generalization—0
Communication-Efficient Distributed Kalman Filtering using ADMM—0
Distributed Model Predictive Control Design for Multi-agent Systems via Bayesian Optimization—0
Distributed Convex Optimization with State-Dependent (Social) Interactions over Random Networks—0
FedCFA: Alleviating Simpson's Paradox in Model Aggregation with Counterfactual Federated LearningCode1
Accelerated Methods with Compressed Communications for Distributed Optimization Problems under Data Similarity—0
Towards privacy-preserving cooperative control via encrypted distributed optimization—0
Information-Geometric Barycenters for Bayesian Federated Learning—0
Deep Distributed Optimization for Large-Scale Quadratic Programming—0
Fractional Order Distributed Optimization—0
Review of Mathematical Optimization in Federated Learning—0
Problem-dependent convergence bounds for randomized linear gradient compression—0
Optimization Algorithm Design via Electric CircuitsCode1
Logarithmically Quantized Distributed Optimization over Dynamic Multi-Agent Networks—0
Tighter Performance Theory of FedExProx—0
Byzantine-Resilient Output Optimization of Multiagent via Self-Triggered Hybrid Detection Approach—0
FedECADO: A Dynamical System Model of Federated Learning—0
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