Information-Theoretic Methods in Data Science
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Published By Cambridge University Press

9781108616799, 9781108427135
Latest Documents Most Cited Documents Contributed Authors Related Sources Related Keywords

scholarly journals Uncertainty Relations and Sparse Signal Recovery

2021 ◽  
pp. 163-196
Author(s):  
Erwin Riegler ◽  
Helmut Bökei
Keyword(s):  
Sparse Signal ◽  
Sparse Signal Recovery ◽  
Uncertainty Relations ◽  
Signal Recovery

Information Bottleneck and Representation Learning

2021 ◽  
pp. 330-358
Author(s):  
Pablo Piantanida ◽  
Leonardo Rey Vega
Keyword(s):  
Representation Learning ◽  
Information Bottleneck

Fundamental Limits in Model Selection for Modern Data Analysis

2021 ◽  
pp. 359-382
Author(s):  
Jie Ding ◽  
Yuhong Yang ◽  
Vahid Tarokh
Keyword(s):  
Data Analysis ◽  
Model Selection ◽  
Fundamental Limits ◽  
Selection For

Computing Choice: Learning Distributions over Permutations

2021 ◽  
pp. 229-262
Author(s):  
Devavrat Shah

Preface

2021 ◽  
pp. xiii-xvi

Information-Theoretic Bounds on Sketching

2021 ◽  
pp. 104-133
Author(s):  
Mert Pilanci
Keyword(s):  
Information Theoretic

Universal Clustering

2021 ◽  
pp. 263-301
Author(s):  
Ravi Kiran Raman ◽  
Lav R. Varshney

An Information-Theoretic Approach to Analog-to-Digital Compression

2021 ◽  
pp. 44-71
Author(s):  
Alon Kipnis ◽  
Yonina C. Eldar ◽  
Andrea J. Goldsmith
Keyword(s):  
Theoretic Approach ◽  
Analog To Digital ◽  
Information Theoretic ◽  
Digital Compression ◽  
Information Theoretic Approach

Compressed Sensing via Compression Codes

2021 ◽  
pp. 72-103
Author(s):  
Shirin Jalali ◽  
H. Vincent Poor
Keyword(s):  
Compressed Sensing

Information-Theoretic Stability and Generalization

2021 ◽  
pp. 302-329
Author(s):  
Maxim Raginsky ◽  
Alexander Rakhlin ◽  
Aolin Xu
Keyword(s):  
Information Theoretic
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