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Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning series)【並行輸入品】

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『Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning series)【並行輸入品】』はセカイモンでolzkzxmuから出品され、64の入札を集めて12月31日 17時 53分に、18840円で落札されました。即決価格は18840円でした。決済方法はに対応。山梨県からの発送料は落札者が負担しました。ＰＲオプションはストア、取りナビ(ベータ版)を利用したオークション、即買でした。

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■全国送料無料■並行輸入品のため、海外からのお取り寄せとなり、配送まで10-20日ほどのお時間を頂いておりますが、迅速配達を心掛けお届けいたします。■詳しい納期は、事前にお問い合わせいただくか、ご購入後にお知らせいたします。■関税につきまして、お客様の負担は一切ございませんのでご安心ください。■海外からの輸送により外箱に若干のいたみ等が出る場合がございますが、商品自体には問題はございません。■税関にて内容確認のため開封される場合がございますが、商品に影響が出るような事はございませんのでご安心くださいませ。

A comprehensive and self-contained introduction to Gaussian processes, which provide a principled, practical, probabilistic approach to learning in kernel machines.Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning community over the past decade, and this book provides a long-needed systematic and unified treatment of theoretical and practical aspects of GPs in machine learning. The treatment is comprehensive and self-contained, targeted at researchers and students in machine learning and applied statistics. The book deals with the supervised-learning problem for both regression and classification, and includes detailed algorithms. A wide variety of covariance (kernel) functions are presented and their properties discussed. Model selection is discussed both from a Bayesian and a classical perspective. Many connections to other well-known techniques from machine learning and statistics are discussed, including support-vector machines, neural networks, splines, regularization networks, relevance vector machines and others. Theoretical issues including learning curves and the PAC-Bayesian framework are treated, and several approximation methods for learning with large datasets are discussed. The book contains illustrative examples and exercises, and code and datasets are available on the Web. Appendixes provide mathematical background and a discussion of Gaussian Markov processes.",

Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning series)【並行輸入品】