Algorithmic Aspects of Machine Learning (Paperback)

Ankur Moitra

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商品描述

This book bridges theoretical computer science and machine learning by exploring what the two sides can teach each other. It emphasizes the need for flexible, tractable models that better capture not what makes machine learning hard, but what makes it easy. Theoretical computer scientists will be introduced to important models in machine learning and to the main questions within the field. Machine learning researchers will be introduced to cutting-edge research in an accessible format, and gain familiarity with a modern, algorithmic toolkit, including the method of moments, tensor decompositions and convex programming relaxations. The treatment beyond worst-case analysis is to build a rigorous understanding about the approaches used in practice and to facilitate the discovery of exciting, new ways to solve important long-standing problems.

商品描述(中文翻譯)

這本書通過探索理論計算機科學和機器學習之間的關聯,將兩者之間的互相學習進行了橋梁。它強調了對於靈活且可處理的模型的需求,這些模型能更好地捕捉到機器學習的易難之處。理論計算機科學家將會介紹到機器學習中的重要模型以及該領域的主要問題。機器學習研究人員將以易於理解的形式介紹最前沿的研究,並熟悉現代算法工具包,包括矩法、張量分解和凸規劃放鬆。這本書不僅僅局限於最壞情況分析,而是建立了對實踐中使用的方法的嚴謹理解,並促進了對於解決重要而長期存在的問題的新方法的發現。