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 101–150 of 536 papers

TitleStatusHype
Combining Graph Attention Networks and Distributed Optimization for Multi-Robot Mixed-Integer Convex Programming—0
Approximate Gradient Coding with Optimal Decoding—0
A primal-dual method for conic constrained distributed optimization problems—0
Communication/Computation Tradeoffs in Consensus-Based Distributed Optimization—0
Communication-Efficient Accurate Statistical Estimation—0
Communication Efficient, Differentially Private Distributed Optimization using Correlation-Aware Sketching—0
Communication-Efficient Distributed Optimization of Self-Concordant Empirical Loss—0
A Provably Communication-Efficient Asynchronous Distributed Inference Method for Convex and Nonconvex Problems—0
Algorithm Unrolling-Based Distributed Optimization for RIS-Assisted Cell-Free Networks—0
A Reinforcement Learning Approach to Parameter Selection for Distributed Optimal Power Flow—0
Adaptive Consensus ADMM for Distributed Optimization—0
Communication-Efficient Distributed Kalman Filtering using ADMM—0
A Sequential Approximation Framework for Coded Distributed Optimization—0
Communication-Efficient Distributed SGD with Compressed Sensing—0
Communication Efficient Federated Learning via Ordered ADMM in a Fully Decentralized Setting—0
Communication Efficient Federated Learning with Linear Convergence on Heterogeneous Data—0
Communication-Efficient Projection-Free Algorithm for Distributed Optimization—0
Communication-efficient Variance-reduced Stochastic Gradient Descent—0
Auction-based and Distributed Optimization Approaches for Scheduling Observations in Satellite Constellations with Exclusive Orbit Portions—0
Concentration of Non-Isotropic Random Tensors with Applications to Learning and Empirical Risk Minimization—0
Consensus optimization approach for distributed Kalman filtering: performance recovery of centralized filtering with proofs—0
Continual Learning with Distributed Optimization: Does CoCoA Forget?—0
Convergence rate of sign stochastic gradient descent for non-convex functions—0
Convergence Rates of Two-Time-Scale Gradient Descent-Ascent Dynamics for Solving Nonconvex Min-Max Problems—0
Convergence Theory of Flexible ALADIN for Distributed Optimization—0
Convergence Theory of Generalized Distributed Subgradient Method with Random Quantization—0
AttentionX: Exploiting Consensus Discrepancy In Attention from A Distributed Optimization Perspective—0
ALADIN-β: A Distributed Optimization Algorithm for Solving MPCC Problems—0
A Tight Convergence Analysis for Stochastic Gradient Descent with Delayed Updates—0
Asynchronous Stochastic Optimization Robust to Arbitrary Delays—0
ALADIN-α -- An open-source MATLAB toolbox for distributed non-convex optimization—0
A continuous-time analysis of distributed stochastic gradient—0
Accelerating Distributed Optimization: A Primal-Dual Perspective on Local Steps—0
Data Encoding for Byzantine-Resilient Distributed Optimization—0
Asynchronous Iterations in Optimization: New Sequence Results and Sharper Algorithmic Guarantees—0
CSWA: Aggregation-Free Spatial-Temporal Community Sensing—0
A KL-based Analysis Framework with Applications to Non-Descent Optimization Methods—0
A Computation and Communication Efficient Method for Distributed Nonconvex Problems in the Partial Participation Setting—0
Cost-efficient SVRG with Arbitrary Sampling—0
Correlation Aware Sparsified Mean Estimation Using Random Projection—0
Asynchronous Forward Bounding for Distributed COPs—0
DC-DistADMM: ADMM Algorithm for Constrained Distributed Optimization over Directed Graphs—0
Decentralized Feature-Distributed Optimization for Generalized Linear Models—0
Decentralized Federated Learning via MIMO Over-the-Air Computation: Consensus Analysis and Performance Optimization—0
Decentralized gradient methods: does topology matter?—0
Decentralized Optimization on Compact Submanifolds by Quantized Riemannian Gradient Tracking—0
Decentralized Optimization with Distributed Features and Non-Smooth Objective Functions—0
Decentralized Personalized Federated Learning for Min-Max Problems—0
Correlated Quantization for Faster Nonconvex Distributed Optimization—0
Correlated quantization for distributed mean estimation and optimization—0
Show:102550
← PrevPage 3 of 11Next →

No leaderboard results yet.