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The chapters in this volume highlight the state-of-the-art of compressed sensing and are based on talks given at the third international MATHEON conference on the same topic, held from December 4-8, 2017 at the Technical University in Berlin.
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Describes in detail the fundamental mathematics and algorithms of machine learning (an example of artificial... Læs mere
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Understanding when and why algorithms work is a fundamental challenge. For problems ranging from clustering to linear programming to neural networks there are... Læs mere
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P-splines are widely used in statistics and machine learning for smoothing out noise in data and to avoid overtraining. This practical guide covers theory and a... Læs mere
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This book presents a comprehensive and consistent theory of estimation. The framework described leads naturally to a powerful new tool, the generalized maximum capacity... Læs mere
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This accessible but rigorous introduction is written for advanced undergraduates and beginning graduate students in data... Læs mere
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Understand fundamental and advanced statistical and deep learning models for robust speaker recognition and domain adaptation. Presenting state-of-the-art machine... Læs mere
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The first unified treatment of the interface between information theory and emerging topics in data science, written in a clear, tutorial style. Covering... Læs mere
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Introduces fundamental concepts, major models, and popular applications of pattern recognition for a one-semester undergraduate course. The text... Læs mere
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This book provides some important findings about the general patterns of use of Bengali morphemes and sheds new light on the form and function of morphemes in... Læs mere