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نویسندگان
چکیده
منابع مشابه
Density Ratio Estimation in Machine Learning
Machine learning is an interdisciplinary field of science and engineering that studies mathematical theories and practical applications of systems that learn. This book introduces theories, methods, and applications of density ratio estimation, which is a newly emerging paradigm in the machine learning community. Various machine learning problems such as non-stationarity adaptation, outlier det...
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In this work, we deal with a relatively new statistical tool in machine learning: the estimation of the ratio of two probability densities, or density ratio estimation for short. As a side piece of research that gained its own traction, we also tackle the task of parameter selection in learning algorithms based on kernel methods. 1 Density Ratio Estimation The estimation of the ratio of two pro...
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A new general framework of statistical data processing based on the ratio of probability densities has been proposed recently and gathers a great deal of attention in the machine learning and data mining communities [1–17]. This density ratio framework includes various statistical data processing tasks such as non-stationarity adaptation [18, 1, 2, 4, 13], outlier detection [19–21, 6], and cond...
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Density ratio estimation has attracted a great deal of attention in the statistics and machine learning communities since it can be used for solving various statistical data processing tasks such as non-stationarity adaptation, two-sample test, outlier detection, independence test, feature selection/extraction, independent component analysis, causal inference, and conditional probability estima...
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