Описание: The dramatic growth in practical applications for machine learning over the last ten years has been accompanied by many important developments in the underlying algorithms and techniques. For example, Bayesian methods have grown from a specialist niche to become mainstream, while graphical models have emerged as a general framework for describing and applying probabilistic techniques. The practical applicability of Bayesian methods has been greatly enhanced by the development of a range of approximate inference algorithms such as variational Bayes and expectation propagation, while new models based on kernels have had a significant impact on both algorithms and applications.A forthcoming companion volume will deal with practical aspects of pattern recognition and machine learning, and will include free software implementations of the key algorithms along with example data sets and demonstration programs.Christopher Bishop is Assistant Director at Microsoft Research Cambridge, and also holds a Chair in Computer Science at the University of Edinburgh. He is a Fellow of Darwin College Cambridge, and was recently elected Fellow of the Royal Academy of Engineering. The author's previous textbook "Neural Networks for Pattern Recognition" has been widely adopted.Coming soon:*For students, worked solutions to a subset of exercises available on a public web site (for exercises marked "www" in the text)*For instructors, worked solutions to remaining exercises from the Springer web site*Lecture slides to accompany each chapter*Data sets available for download
Автор: Bishop, Christopher M. Название: Neural Networks for Pattern Recognition ISBN: 0198538642 ISBN-13(EAN): 9780198538646 Издательство: Oxford Academ Рейтинг: Цена: 4683 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Providing a comprehensive account of neural networks from a statistical perspective, this book emphasizes on pattern recognition, which represents the area of greatest applicability for neural networks in contemporary times.
Автор: Brian D. Ripley Название: Pattern Recognition and Neural Networks ISBN: 0521717701 ISBN-13(EAN): 9780521717700 Издательство: Cambridge Academ Рейтинг: Цена: 3746 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Now in paperback: the most reliable account of the statistical framework for pattern recognition and machine learning. With unparalleled coverage and a wealth of case-studies this book gives valuable insight into both the theory and the enormously diverse applications (which can be found in remote sensing, astrophysics, engineering and medicine, for example). So that readers can develop their skills and understanding, many of the real data sets used in the book are available from the author’s website: www.stats.ox.ac.uk/~ripley/PRbook/. For the same reason, many examples are included to illustrate real problems in pattern recognition. Unifying principles are highlighted, and the author gives an overview of the state of the subject, making the book valuable to experienced researchers in statistics, machine learning/artificial intelligence and engineering. The clear writing style means that the book is also a superb introduction for non-specialists.
Описание: Introduction to Pattern Recognition: A Matlab Approach is an accompanying manual to Theodoridis/Koutroumbas' Pattern Recognition. It includes Matlab code of the most common methods and algorithms in the book, together with a descriptive summary and solved examples, and including real-life data sets in imaging and audio recognition. This text is designed for electronic engineering, computer science, computer engineering, biomedical engineering and applied mathematics students taking graduate courses on pattern recognition and machine learning as well as R&D engineers and university researchers in image and signal processing/analyisis, and computer vision.
Автор: Sergios Theodoridis Название: Pattern Recognition, ISBN: 1597492728 ISBN-13(EAN): 9781597492720 Издательство: Elsevier Science Рейтинг: Цена: 8410 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book considers classical and current theory and practice, of supervised, unsupervised and semi-supervised pattern recognition, to build a complete background for professionals and students of engineering. The authors, leading experts in the field of pattern recognition, have provided an up-to-date, self-contained volume encapsulating this wide spectrum of information. The very latest methods are incorporated in this edition: semi-supervised learning, combining clustering algorithms, and relevance feedback. . · Thoroughly developed to include many more worked examples to give greater understanding of the various methods and techniques. . · Many more diagrams included--now in two color--to provide greater insight through visual presentation. . . · Matlab code of the most common methods are given at the end of each chapter. . . . . . · More Matlab code is available, together with an accompanying manual, via this site . . . . · Latest hot topics included to further the reference value of the text including non-linear dimensionality reduction techniques, relevance feedback, semi-supervised learning, spectral clustering, combining clustering algorithms. . · An accompanying book with Matlab code of the most common methods and algorithms in the book, together with a descriptive summary, and solved examples including real-life data sets in imaging, and audio recognition. The companion book will be available separately or at a special packaged price (ISBN: 9780123744869).
Описание: This book constitutes the refereed proceedings of the 4th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2005, held in Leipzig, Germany, in July 2005.The 68 revised full papers presented were carefully reviewed and selected. The papers are organized in topical sections on classification and model estimation, neural methods, subspace methods, basics and applications of clustering, feature grouping, discretization, selection and transformation, applications in medicine, time series and sequential pattern mining, mining images in computer vision, mining images and texture, mining motion from sequence, speech analysis, aspects of data mining, text mining, and as a special track: industrial applications of data mining.
Описание: This book constitutes the refereed proceedings of the 5th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2007, held in Leipzig, Germany, in July 2007.The 66 revised full papers presented together with 1 invited talk were carefully reviewed and selected from 258 submissions. The papers are organized in topical sections on classification; feature selection, extraction and dimensionality reduction; clustering; support vector machines; transductive inference; association rule mining; mining spam, newsgroups, blogs; intrusion detection and networks; frequent and common item set mining; mining marketing data; structural data mining; image mining; medical, biological, and environmental data mining; as well as text and document mining.
Описание: This book constitutes the refereed proceedings of the Second International Workshop on Machine Learning and Data Mining in Pattern Recognition, MLDM 2001, held in Leipzig, Germany in July 2001.The 26 revised full papers presented together with two invited papers were carefully reviewed and selected for inclusion in the proceedings. The papers are organized in topical sections on case-based reasoning and associative memory; rule induction and grammars; clustering and conceptual clustering; data mining on signals, images, and spatio-temporal data; nonlinear function learning and neural net based learning; learning for handwriting recognition; statistical and evolutionary learning; and content-based image retrieval.
Описание: This book constitutes the refereed proceedings of the Third International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2003, held in Leipzig, Germany, in July 2003.The 33 revised full papers presented together with two invited papers were carefully reviewed and selected from 75 submissions. The papers are organized in topical sections on decision trees; clustering and its applications; support vector machines; case-based reasoning; classification, retrieval, and feature Learning; discovery of frequent or sequential patterns; Bayesian models and methods; association rule mining; and applications.
Описание: This book constitutes the refereed proceedings of the 5th International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition, EMMCVPR 2005, held in St. Augustine, FL, USA in November 2005.The 24 revised full papers and 18 poster papers presented were carefully reviewed and selected from 120 submissions. The papers are organized in topical sections on probabilistic and informational approaches, combinatorial approaches, variational approaches, and other approaches and applications.
Описание: Part I: Diaspora Overviews. African Diaspora in Asia; G. Campbell. African Diaspora in Europe; D. Gnammankou. African Diaspora in the Americas; K.A. Yelvington. Armenian Diaspora; K. TГ¶lГ¶lyan. British Diaspora; E. Richards. Chilean Diaspora; T.C. Wright, R. Onate. Chinese Diaspora; A. McKeown. Croatian Diaspora; D. Winland. Greek Diaspora; I. Laliotou. Hakka Diaspora; E. Lozada. Hmong Diaspora; N. Tapp. Hui Diaspora; R. Ma. Irish Diaspora; N. Farley, P. Kilbride. Israeli Diaspora; R. Cohen. Italian Diaspora; D.R. Gabaccia. Jewish Diaspora in China; Xin Xu. Jewish Diaspora in Europe and the Americas; M.J. Konner. Jewish Diaspora in the Ancient World, Africa, and Asia; M.J. Konner. Jewish Diaspora in the Greek World; S. Bowman. Korean Diaspora; In Jin Yoon. Kurdish Diaspora; A. Hassanpour, S. Mojab. Oceanian Diasporas; D.A. Chappell. Palestinian Diaspora; S. Farsoun. Philippine Diaspora; R. Lawless. Polish Diaspora; D. Pacyga. Post-Soviet Russian Diaspora; N. Kosmarskaya. Sikh Diaspora; D. Singh Tatla. South Asian Diaspora; P. Rangaswamy. Swiss Diaspora; L. Schelbert. Tuareg Diaspora; S. Rasmussen. Yoruba Diaspora; K. Abimbola. Part II: Topics. Arts in Diasporas:- Art of the African Diaspora; M. Harris. Chinese Diaspora Memoirs in the United States; King Fai Tam. Dance in the African Diaspora; Y. Daniel. Literature of Korean Diaspora in Japan; Choonmie Kim. Music of the African Diaspora in the Americas; D. Hill. South Asian Diaspora in Film; J. Desai. Women and Literature in the African Diaspora; C. Boyce Davies. Diaspora Politics and Identity:- Chinese Diaspora Politics and its Fallout in a Cyber Age; Aihwa Ong. Creating a Diaspora within a Country: Kurds in Turkey; C. Houston. Diasporas and Human Rights; P. Magnarella. Diasporas and International Agencies; M. Leopold. Diasporic Consciousness Among African-Americans; J. Glazier. Emerging Diaspora Consciousness Among African Canadians in Toronto; R. Walcott. Hindu Diaspora in the United States; A. Rajagopal. Jewish-American Identity and Israeli Security: Diasporic Connections; Y. Shain. Jews and Christians in Germany; H. Thomann Tewarson. Pakistani Migration and Diaspora Religious Politics in a Global Age; P. Werbner. Sikh Positionings in Australia and the "Diaspora" Concept; V.A. Dusenbery. Tamil Diaspora Politics; D. Sriskandarajah. Global Cities:- Global Cities and Diasporic Networks; S. Sassen. Hong Kong; J. Bosco. Jews in Kaifeng, China; Xin Xu. Miami Diasporas; L. Konczal. Types of Diaspora:- Asylum Diaspora: Tamils in Switzerland; C. McDowell. Chaordic Diasporas; P. Werbner. Congolese Traders: Unofficial Immigrants in France; J. MacGaffey. Diasporas and Globalization; D.M. Nonini. Long-Distance Nationalism; N. Glick Schiller. Refugee Diasporas; N. Van Hear. Part III: Diaspora Communities. African Diaspora in the Netherlands; A. Blakely. Brazilians in the United States, Canada, Europe, Japan and Paraguay; M. Margolis. Cape Verdeans in the United States; M. Halter. Caribbeans in the United Kingdom; C. Peach. Chinese in Australia; H. Chan. Chinese in Canada; J.-A. Lee, Xiaoping Li. Chinese in Europe; Minghuan Li. Chinese in Hungary; P. Nyíri. Chinese in India; E. Oxfeld. Chinese in Japan; L. Tien-shi. Chinese in Korea; Kwang-ok Kim. Chinese in Malaysia; Chee Beng Tan. Chinese in Papua New Guinea; D.Y.H. Wu. Chinese in Russia; A. Dikariov. Chinese in Singapore; Chee Kiong Tong. Chinese in South Africa; K. Leigh Harris. Chinese in Tahiti; Yuan-chao Tung. Chinese in Thailand; Jiemen Bao. Chinese in the Philippines; T. Ang See. Chinese in the United States; Ling-chi Wang. Eritreans in the Sudan; G. Kibreab. Ethnic Chinese in Indonesia; M.G.Tan. Filipinos in Japan; J. Anderson. Greeks in Canada; A.N. Panagakos. Haitians in the United States; M.S. Laguerre. Indians in Fiji; A.R Walker. Italians in Australia; L. Baldassar. Italians in Canada; J. Zucchi. Italians in the United Kingdom; L. Sponza. Italians in the United States; V. Pagliai. Jamaicans in the United States; M. Vickerman. Japanese in Brazil; N. Adachi. Japanese in the United States; W. Ng. Jews from Rhodes in Central and Southern Africa; R. Hirschon. Jews in Denmark; T. Lichtenstein. Jews in France; J. Bahloul. Jews in Latin America; A. Ben-Ur. Jews in Morocco; E. Gottreich. Koreans in Japan; S. Ryang. Koreans in Kazakhstan, Uzbekistan, and Russia; G. Kim. Koreans in the United States; Kyeyoung Park. Kurds in Finland; O. Wahlbeck. Kurds in Germany; B. Ammann. Latinos in Japan; R. Reyes-Ruiz. Mexicans in the United States; R. Van Kemper, W. Pulte. Neo-Orthodox Jews of Germany; S. Deshen. Nuer in the United States; D. Shandy. Puerto Ricans in the United States; J. Duany. Roma in the United States; A. Sutherland. Sikhs in Canada; H. Johnston. Sikhs in the United Kingdom; D. Singh Tatla. Sikhs in the United States; B. LaBrack. South Asians in Malaysia and Singapore; A.R. Walker. Tibetans in India; D. de Voe. Turks in Germany; W. Schiffauer. Vietnamese in Australia; M. Thomas. Vietnamese in Canada; L.-J. Dorais. Vietnamese in France; M.E. Blanc.
Описание: Dynamic Fuzzy Pattern Recognition with Applications to Finance and Engineering focuses on fuzzy clustering methods which have proven to be very powerful in pattern recognition and considers the entire process of dynamic pattern recognition. This book sets a general framework for Dynamic Pattern Recognition, describing in detail the monitoring process using fuzzy tools and the adaptation process in which the classifiers have to be adapted, using the observations of the dynamic process. It then focuses on the problem of a changing cluster structure (new clusters, merging of clusters, splitting of clusters and the detection of gradual changes in the cluster structure). Finally, the book integrates these parts into a complete algorithm for dynamic fuzzy classifier design and classification.
ООО "Логосфера " Тел:+7(495) 980-12-10 www.logobook.ru