A self-contained and coherent account of probabilistic techniques, covering: distance measures, kernel rules, nearest neighbour rules, Vapnik-Chervonenkis theory, parametric classification, and feature extraction. Each chapter concludes with problems and exercises to further the readers understanding. Both research workers and graduate students will benefit from this wide-ranging and up-to-date account of a fast- moving field.
This important text and reference for researchers and students in machine learning, game theory, statistics and information theory offers a comprehensive treatment of the problem of predicting individual sequences. Unlike standard statistical approaches to forecasting, prediction of individual sequences does not impose any probabilistic assumption on the data-generating mechanism. Yet, prediction algorithms can be constructed that work well for all possible sequences, in the sense that their performance is always nearly as good as the best forecasting strategy in a given reference class. The central theme is the model of prediction using expert advice, a general framework within which many related problems can be cast and discussed. Repeated game playing, adaptive data compression, sequential investment in the stock market, sequential pattern analysis, and several other problems are viewed as instances of the experts' framework and analyzed from a common nonstochastic standpoint that often reveals new and intriguing connections.
Density estimation has evolved enormously since the days of bar plots and histograms, but researchers and users are still struggling with the problem of the selection of the bin widths. This book is the first to explore a new paradigm for the data-based or automatic selection of the free parameters of density estimates in general so that the expected error is within a given constant multiple of the best possible error. The paradigm can be used in nearly all density estimates and for most model selection problems, both parametric and nonparametric.
The Stigmata of Auschwitz is the brief story of the life and love of Rebekah and Gabriel. The two main characters of the story are a young Jewish couple whose lives bringing up their young child are cut short and sacrificed to an evil Nazi ideology. The story takes place between March 1938 to September 1941, in the time of the Shoah (the Holocaust). Gabriel is from Budapest in Hungary, where he is sent on a mission to Munkács in Western Ukraine. There he meets Rebekah. They fall in love, marry, and settle in Munkács, where the population is 42% Jewish. In Munkács, Gabriel and Rebekah build up a successful business and public life: he becomes a councillor representing the Jewish community, while she is a member of the Union of Jewish Women. To complete their enviable lifestyle, they have a much-loved baby son. But their dream is destroyed by the antisemitism unleashed at the outbreak of the Second World War; their life together is ruined by the ruling fascist elite. Consequently, they departed to Auschwitz, where they are murdered. However, their two-year-old son is rescued and raised by their neighbour.
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