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＜電子ブック＞
Compressed Sensing and Its Applications : Third International MATHEON Conference 2017 / edited by Holger Boche, Giuseppe Caire, Robert Calderbank, Gitta Kutyniok, Rudolf Mathar, Philipp Petersen
(Applied and Numerical Harmonic Analysis. ISSN:22965017)

版	1st ed. 2019.
出版者	(Cham : Springer International Publishing : Imprint: Birkhäuser)
出版年	2019
本文言語	英語
大きさ	XVII, 295 p. 57 illus., 39 illus. in color : online resource
著者標目	Boche, Holger editor Caire, Giuseppe editor Calderbank, Robert editor Kutyniok, Gitta editor Mathar, Rudolf editor Petersen, Philipp editor SpringerLink (Online service)
件　名	LCSH:Computer science -- Mathematics  全ての件名で検索 LCSH:Fourier analysis LCSH:Machine learning LCSH:Signal processing FREE:Mathematical Applications in Computer Science FREE:Fourier Analysis FREE:Machine Learning FREE:Signal, Speech and Image Processing
一般注記	An Introduction to Compressed Sensing -- Quantized Compressed Sensing: a Survey -- On reconstructing functions from binary measurements -- Classification scheme for binary data with extensions -- Generalization Error in Deep Learning -- Deep learning for trivial inverse problems -- Oracle inequalities for local and global empirical risk minimizers -- Median-Truncated Gradient Descent: A Robust and Scalable Nonconvex Approach for Signal Estimation -- Reconstruction Methods in THz Single-pixel Imaging 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. In addition to methods in compressed sensing, chapters provide insights into cutting edge applications of deep learning in data science, highlighting the overlapping ideas and methods that connect the fields of compressed sensing and deep learning. Specific topics covered include: Quantized compressed sensing Classification Machine learning Oracle inequalities Non-convex optimization Image reconstruction Statistical learning theory This volume will be a valuable resource for graduate students and researchers in the areas of mathematics, computer science, and engineering, as well as other applied scientists exploring potential applications of compressed sensing HTTP:URL=https://doi.org/10.1007/978-3-319-73074-5

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