SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 251–275 of 536 papers

TitleStatusHype
Distributed gradient-based optimization in the presence of dependent aperiodic communication—0
Distributed Learning of Generalized Linear Causal Networks—0
Coordinated Day-ahead Dispatch of Multiple Power Distribution Grids hosting Stochastic Resources: An ADMM-based Framework—0
Distributed Random Reshuffling over Networks—0
Convergence Rates of Two-Time-Scale Gradient Descent-Ascent Dynamics for Solving Nonconvex Min-Max Problems—0
Communication-Efficient Distributed SGD with Compressed Sensing—0
Distributed Graph Learning with Smooth Data Priors—0
Collaborative Learning over Wireless Networks: An Introductory Overview—0
Variance Reduction in Deep Learning: More Momentum is All You Need—0
FLIX: A Simple and Communication-Efficient Alternative to Local Methods in Federated Learning—0
A Semi-Distributed Interior Point Algorithm for Optimal Coordination of Automated Vehicles at Intersections—0
Finite-Time Consensus Learning for Decentralized Optimization with Nonlinear Gossiping—0
Basis Matters: Better Communication-Efficient Second Order Methods for Federated Learning—0
Decentralized Feature-Distributed Optimization for Generalized Linear Models—0
Cell Zooming with Masked Data for Off-Grid Small Cell Networks: Distributed Optimization Approach—0
Parallel Feedforward Compensation for Output Synchronization: Fully Distributed Control and Indefinite Laplacian—0
Acceleration in Distributed Optimization under Similarity—0
A Reinforcement Learning Approach to Parameter Selection for Distributed Optimal Power Flow—0
Utilizing Redundancy in Cost Functions for Resilience in Distributed Optimization and Learning—0
Distributed Optimization of Graph Convolutional Network using Subgraph Variance—0
KKT Conditions, First-Order and Second-Order Optimization, and Distributed Optimization: Tutorial and Survey—0
Distributed Privacy-Preserving Electric Vehicle Charging Control Based on Secret Sharing—0
Distributed Optimization using Heterogeneous Compute SystemsCode0
Unbiased Single-scale and Multi-scale Quantizers for Distributed OptimizationCode1
Communication-Efficient Federated Linear and Deep Generalized Canonical Correlation AnalysisCode0
Show:102550
← PrevPage 11 of 22Next →

No leaderboard results yet.