1.

Record Nr.

UNINA9910349322703321

Titolo

Compressed Sensing and Its Applications : Third International MATHEON Conference 2017 / / edited by Holger Boche, Giuseppe Caire, Robert Calderbank, Gitta Kutyniok, Rudolf Mathar, Philipp Petersen

Pubbl/distr/stampa

Cham : , : Springer International Publishing : , : Imprint : Birkhäuser, , 2019

ISBN

3-319-73074-6

Edizione

[1st ed. 2019.]

Descrizione fisica

1 online resource (305 pages)

Collana

Applied and Numerical Harmonic Analysis, , 2296-5009

Disciplina

621.38220151

Soggetti

Information theory

Fourier analysis

Computer science—Mathematics

Computer science - Mathematics

Machine learning

Signal processing

Image processing

Speech processing systems

Information and Communication, Circuits

Fourier Analysis

Mathematical Applications in Computer Science

Machine Learning

Signal, Image and Speech Processing

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di bibliografia

Includes bibliographical references.

Nota di contenuto

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.

Sommario/riassunto

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.

2.

Record Nr.

UNINA9910958147703321

Autore

Klarman Michael J.

Titolo

Brown v. Board of Education and the civil rights movement : abridged edition of From Jim Crow to civil rights : the Supreme Court and the struggle for racial equality / / Michael J. Klarman

Pubbl/distr/stampa

Oxford ; , : Oxford University Press, , 2023

ISBN

0-19-771853-1

0-19-029458-2

1-281-16337-6

9786611163372

0-19-804200-0

1-4356-0585-3

Descrizione fisica

1 online resource

Collana

Oxford scholarship online

Altri autori (Persone)

KlarmanMichael J

Disciplina

344.73/0798

Soggetti

Segregation - Law and legislation - United States - History - 20th century

United States Race relations History 20th century

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Previously issued in print: 2007.



Nota di bibliografia

Includes bibliographical references (pages 263-271) and index.

Nota di contenuto

The Jim Crow Era -- World War II -- Brown v. Board of Education -- Brown II and subsequent desegregation developments -- Brown's direct effects -- Brown's indirect effects -- Brown's backlash -- Why massive resistance? -- Brown, violence, and civil rights legislation.

Sommario/riassunto

A splendid account of the Supreme Court's rulings on race in the first half of the twentieth century, From Jim Crow To Civil Rights earned rave reviews and won the Bancroft Prize for History in 2005. Now, in this marvelously abridged, paperback edition, Michael J. Klarman has compressed his acclaimed study into tight focus around one major case--Brown v. Board of Education--making the path-breaking arguments of his original work accessible to a broader audience of general readers and students.