A STUDY ON THE ERROR OF DISTRIBUTED ALGORITHMS FOR BIG DATA CLASSIFICATION WITH SVM

DOI10.1017/S1446181116000390zbMath1418.68181OpenAlexW4253073180MaRDI QIDQ5370777

Cheng Wang, Feilong Cao

Publication date: 20 October 2017

Published in: The ANZIAM Journal (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1017/s1446181116000390

zbMATH Keywords

distributed algorithmbig datasupport vector machinegeometric noise exponenttsybakov exponent

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Distributed algorithms (68W15)

Cites Work

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• Model selection for regularized least-squares algorithm in learning theory
• Fast rates for support vector machines using Gaussian kernels
• Divide and Conquer Kernel Ridge Regression: A Distributed Algorithm with Minimax Optimal Rates
• Learning Theory
• Convexity, Classification, and Risk Bounds

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