scientific article; zbMATH DE number 6982986

zbMath1473.68167arXiv1611.02189MaRDI QIDQ4558572

Virginia Smith, Martin Takáč, Martin Jaggi, Chenxin Ma, Simone Forte, Michael I. Jordan

Publication date: 22 November 2018

Full work available at URL: https://arxiv.org/abs/1611.02189

Title: zbMATH Open Web Interface contents unavailable due to conflicting licenses.

zbMATH Keywords

convex optimizationdistributed systemsparallel and distributed algorithmslarge-scale machine learning

Mathematics Subject Classification ID

Convex programming (90C25) Learning and adaptive systems in artificial intelligence (68T05) Distributed algorithms (68W15)

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Uses Software

• CoCoA
• LIBLINEAR
• glmnet
• MLlib
• HOGWILD
• Apache Spark
• BLITZ

Cites Work

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• Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
• Smooth minimization of non-smooth functions
• Coordinate descent algorithms
• Techniques of variational analysis
• Distributed Coordinate Descent Method for Learning with Big Data
• A Quasi-Newton Approach to Nonsmooth Convex Optimization Problems in Machine Learning
• Rate Analysis of Inexact Dual First-Order Methods Application to Dual Decomposition
• Accelerated, Parallel, and Proximal Coordinate Descent
• D-ADMM: A Communication-Efficient Distributed Algorithm for Separable Optimization
• Distributed optimization with arbitrary local solvers
• Stochastic Primal-Dual Coordinate Method for Regularized Empirical Risk Minimization
• A General Distributed Dual Coordinate Optimization Framework for Regularized Loss Minimization
• Optimal Distributed Online Prediction using Mini-Batches
• Stochastic Dual Coordinate Ascent Methods for Regularized Loss Minimization
• Convex analysis and monotone operator theory in Hilbert spaces
• Accelerated proximal stochastic dual coordinate ascent for regularized loss minimization