Sharper Bounds for Regularized Data Fitting

DOI10.4230/LIPIcs.APPROX-RANDOM.2017.27zbMath1471.62408arXiv1611.03225OpenAlexW2963020110MaRDI QIDQ5002630

Haim Avron, David P. Woodruff, Kenneth L. Clarkson

Publication date: 28 July 2021

Full work available at URL: https://arxiv.org/abs/1611.03225

zbMATH Keywords

regularizationcanonical correlation analysismatricesregressionlow-rank approximationstatistical learning

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Linear regression; mixed models (62J05) Measures of association (correlation, canonical correlation, etc.) (62H20) Learning and adaptive systems in artificial intelligence (68T05) Numerical methods for low-rank matrix approximation; matrix compression (65F55)

Related Items

Semi-Infinite Linear Regression and Its Applications, Faster Kernel Ridge Regression Using Sketching and Preconditioning, M-IHS: an accelerated randomized preconditioning method avoiding costly matrix decompositions, Randomized Low-Rank Approximation of Monotone Matrix Functions, Unnamed Item

Uses Software

• LowRankModels
• Pyglrm

Cites Work

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