{"product_id":"neural-network-learning-theoretical-foundations-9780521118620","title":"Neural Network Learning: Theoretical Foundations","description":"This important work describes recent theoretical advances in the study of artificial neural networks. It explores probabilistic models of supervised learning problems, and addresses the key statistical and computational questions. Chapters survey research on pattern classification with binary-output networks, including a discussion of the relevance of the Vapnik Chervonenkis dimension, and of estimates of the dimension for several neural network models. In addition, Anthony and Bartlett develop a model of classification by real-output networks, and demonstrate the usefulness of classification with a large margin. The authors explain the role of scale-sensitive versions of the Vapnik Chervonenkis dimension in large margin classification, and in real prediction. Key chapters also discuss the computational complexity of neural network learning, describing a variety of hardness results, and outlining two efficient, constructive learning algorithms. The book is self-contained and accessible to researchers and graduate students in computer science, engineering, and mathematics.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eAuthor:\u003c\/b\u003e \u003ca href=\"https:\/\/correctionsbookstore.com\/search?type=product%2Carticle%2Cpage\u0026amp;q=AUTH-2263915\"\u003eMartin Anthony\u003c\/a\u003e, \u003ca href=\"https:\/\/correctionsbookstore.com\/search?type=product%2Carticle%2Cpage\u0026amp;q=AUTH-3552719\"\u003ePeter L. Bartlett\u003c\/a\u003e\u003cbr\u003e\u003cb\u003ePublisher:\u003c\/b\u003e Cambridge University Press\u003cbr\u003e\u003cb\u003ePublished:\u003c\/b\u003e 08\/20\/2009\u003cbr\u003e\u003cb\u003ePages:\u003c\/b\u003e 404\u003cbr\u003e\u003cb\u003eBinding Type:\u003c\/b\u003e Paperback\u003cbr\u003e\u003cb\u003eWeight:\u003c\/b\u003e 1.30lbs\u003cbr\u003e\u003cb\u003eSize:\u003c\/b\u003e 9.00h x 6.00w x 0.90d\u003cbr\u003e\u003cb\u003eISBN13:\u003c\/b\u003e 9780521118620\u003cbr\u003e\u003cb\u003eISBN10:\u003c\/b\u003e 052111862X\u003cbr\u003e\u003cb\u003eBISAC Categories:\u003c\/b\u003e\u003cbr\u003e- \u003ca href=\"https:\/\/correctionsbookstore.com\/search?type=product%2Carticle%2Cpage\u0026amp;q=CAT-COM\"\u003eComputers\u003c\/a\u003e | \u003ca href=\"https:\/\/correctionsbookstore.com\/search?type=product%2Carticle%2Cpage\u0026amp;q=BISAC-COM016000\"\u003eArtificial Intelligence | Computer Vision \u0026amp; Pattern Recognit\u003c\/a\u003e\u003cbr\u003e- \u003ca href=\"https:\/\/correctionsbookstore.com\/search?type=product%2Carticle%2Cpage\u0026amp;q=CAT-COM\"\u003eComputers\u003c\/a\u003e | \u003ca href=\"https:\/\/correctionsbookstore.com\/search?type=product%2Carticle%2Cpage\u0026amp;q=BISAC-COM044000\"\u003eData Science | Neural Networks\u003c\/a\u003e\u003cbr\u003e- \u003ca href=\"https:\/\/correctionsbookstore.com\/search?type=product%2Carticle%2Cpage\u0026amp;q=CAT-COM\"\u003eComputers\u003c\/a\u003e | \u003ca href=\"https:\/\/correctionsbookstore.com\/search?type=product%2Carticle%2Cpage\u0026amp;q=BISAC-COM043000\"\u003eNetworking | General\u003c\/a\u003e\u003cbr\u003e\u003cp\u003e\u003ci\u003eThis title is not returnable\u003c\/i\u003e\u003cbr\u003e\u003c\/p\u003e","brand":"Cambridge University Press","offers":[{"title":"Default Title","offer_id":45876718960815,"sku":"9780521118620","price":100.58,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0651\/9255\/8767\/files\/img_44c5b525-02f6-44e2-b920-777fd79dadc0.jpg?v=1757694493","url":"https:\/\/www.correctionsbookstore.com\/es\/products\/neural-network-learning-theoretical-foundations-9780521118620","provider":"Corrections Bookstore ","version":"1.0","type":"link"}