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 71–80 of 536 papers

TitleStatusHype
Byzantine-Robust Loopless Stochastic Variance-Reduced GradientCode0
Differentially Private Distributed Estimation and LearningCode0
Efficient Randomized Subspace Embeddings for Distributed Optimization under a Communication BudgetCode0
Distributed Markov Chain Monte Carlo Sampling based on the Alternating Direction Method of MultipliersCode0
Distributed Optimization using Heterogeneous Compute SystemsCode0
CoCoA: A General Framework for Communication-Efficient Distributed OptimizationCode0
Federated Learning: Challenges, Methods, and Future DirectionsCode0
Communication- and Computation-Efficient Distributed Submodular Optimization in Robot Mesh NetworksCode0
FairSync: Ensuring Amortized Group Exposure in Distributed Recommendation RetrievalCode0
Transmission Investment Coordination using MILP Lagrange Dual Decomposition and Auxiliary Problem PrincipleCode0
Show:102550
← PrevPage 8 of 54Next →

No leaderboard results yet.