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9781108461733

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'There is no doubt that this book will change the way people think about machine learning and stimulate many new directions for research.' Thomas G. Dietterich, from the Foreword There is no doubt that this book will change the way people think about machine learning and stimulate many new directions for research. From the Foreword by Thomas G. Dietterich The book is well written and produced, and will probably be seen in retrospect as a significant addition to the literature in this important area--at least to the extent that density ratio estimation as a technique proves useful in real-world applications. Future work and applications using the theory presented should indicate to what extent this happens. Shrisha Rao, Computing Reviews This book is clear and well written, and it is an excellent introduction to density ratio estimation in both theory and practice. It presents the state-of-the-art methodology on this topic and in this regard it is really nice that the bibliography is so exhaustive and well commented. Pierre Alquir, Mathematical Reviews

'There is no doubt that this book will change the way people think about machine learning and stimulate many new directions for research.' Thomas G. Dietterich, from the Foreword

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Masashi Sugiyama is an Associate Professor in the Department of Computer Science at the Tokyo Institute of Technology. Taiji Suzuki is an Assistant Professor in the Department of Mathematical Informatics at the University of Tokyo, Japan. Takafumi Kanamori is an Associate Professor in the Department of Computer Science and Mathematical Informatics at Nagoya University, Japan.

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