Richard Golden

Statistical Machine Learning (eBook, ePUB)

A Unified Framework

• Format: ePub

Produktbeschreibung

This book is a text intended for advanced undergraduates or graduate students which provides theoretical tools for analyzing and designing a large class of supervised, unsupervised, and reinforcement statistical machine learning algorithms using classical theorems from the fields of nonlinear optimization theory and mathematical statistics.

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 524
• Erscheinungstermin: 24. Juni 2020
• Englisch
• ISBN-13: 9781351051484
• Artikelnr.: 59751290

Autorenporträt

Richard M. Golden (Ph.D., M.S.E.E., B.S.E.E.) is Professor of Cognitive Science and Participating Faculty Member in Electrical Engineering at the University of Texas at Dallas. Dr. Golden has published articles and given talks at scientific conferences on a wide range of topics in the fields of both statistics and machine learning over the past three decades. His long-term research interests include identifying conditions for the convergence of deterministic and stochastic machine learning algorithms and investigating estimation and inference in the presence of possibly misspecified probability models.