The book covers new mathematical and computational principles for high-dimensional data analysis (statistics and geometry), scalable optimization methods (convex and nonconvex), and important applications such as scientific imaging, wideband communications, face recognition, 3D vision, and deep networks. This book is to be used as an introductory graduate textbook for the areas...(展开全部)

The book covers new mathematical and computational principles for high-dimensional data analysis (statistics and geometry), scalable optimization methods (convex and nonconvex), and important applications such as scientific imaging, wideband communications, face recognition, 3D vision, and deep networks. This book is to be used as an introductory graduate textbook for the areas...(展开全部)

Modern statistics deals with large and complex data sets, and consequently with models containing a large number of parameters. This book presents a detailed account of recently developed approaches, including the Lasso and versions of it for various models, boosting methods, undirected graphical modeling, and procedures controlling false positive selections. A special characte...(展开全部)

Modern statistics deals with large and complex data sets, and consequently with models containing a large number of parameters. This book presents a detailed account of recently developed approaches, including the Lasso and versions of it for various models, boosting methods, undirected graphical modeling, and procedures controlling false positive selections. A special characte...(展开全部)

Modern statistics deals with large and complex data sets, and consequently with models containing a large number of parameters. This book presents a detailed account of recently developed approaches, including the Lasso and versions of it for various models, boosting methods, undirected graphical modeling, and procedures controlling false positive selections. A special characte...(展开全部)

High-dimensional probability offers insight into the behavior of random vectors, random matrices, random subspaces, and objects used to quantify uncertainty in high dimensions. Drawing on ideas from probability, analysis, and geometry, it lends itself to applications in mathematics, statistics, theoretical computer science, signal processing, optimization, and more. It is the f...(展开全部)

Robert May's seminal book has played a central role in the development of ecological science. Originally published in 1976, this influential text has overseen the transition of ecology from an observational and descriptive subject to one with a solid conceptual core. Indeed, it is a testament to its influence that a great deal of the novel material presented in the earlier edit...(展开全部)

This important new edition is for graduate students studying Molecular Modelling, Computational Chemistry within Chemistry, Medicinal Chemistry and Biochemistry. Postgraduates and researchers in academia and in the chemical and pharmaceutical industries. This new edition introduces background theory and techniques of molecular modelling, also illustrates applications in studyi...(展开全部)

◎ 著者简介 亚瑟·奥沙利文（Arthur O’Sullivan），普林斯顿大学经济学博士，先后在加州大学戴维斯分校 和俄勒冈州立大学任教，现为路易克拉克大学的经济学 教授，是城市经济学领域的著名学者，主要研究与城市 土地使用、环境保护和公共政策相关的经济问题，其著作《城市经济学》畅销全球。 史蒂文·谢弗林（Steven M. Sheffrin），麻省理工学院经济学博士，杜兰大学墨菲学院的经济学 教授，长期担任美国财政部税收分析办公室经济学家， 研究领域包括宏观经济学、公共财政和国际经济学，著有《理性预期》一书。 斯蒂芬·佩雷斯（Stephen J. Perez），加州大学戴维斯分校经济学博士，加利福尼亚州立大学 经济学教授。主要研究领域为宏观经济、体育经济、劳 动经济和计量经济。 ◎ 译者简介 宋迎昌，中国社会科学院生态文明研究所研究员，中国社会科...(展开全部)