Low-rank decomposition meets kernel learning: a generalized Nyström method

DOI10.1016/j.artint.2017.05.001zbMath1419.68077OpenAlexW2616414490MaRDI QIDQ1680675

Peng Zhang

Publication date: 16 November 2017

Published in: Artificial Intelligence (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.artint.2017.05.001

zbMATH Keywords

multiple kernel learningkernel learninglarge-scale learning algorithmsNyström low-rank decomposition

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Related Items (1)

Randomized approximate class-specific kernel spectral regression analysis for large-scale face verification

Uses Software

• LIBSVM
• LIBLINEAR
• SimpleMKL

Cites Work

• On parallel complexity of nonsmooth convex optimization
• Integral equations. Theory and numerical treatment
• Exact matrix completion via convex optimization
• 10.1162/153244303768966085
• 10.1162/15324430260185619
• Fast computation of low rank matrix approximations
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