Information Theoretic Principles for Agent Learning

Specificaties
Gebonden, 150 blz. | Engels
Springer Nature Switzerland | 2024
ISBN13: 9783031653872
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Springer Nature Switzerland e druk, 2024 9783031653872
€ 60,99
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Samenvatting

This book provides readers with the fundamentals of information theoretic techniques for statistical data science analyses and for characterizing the behavior and performance of a learning agent outside of the standard results on communications and compression fundamental limits. Readers will benefit from the presentation of information theoretic quantities, definitions, and results that provide or could provide insights into data science and learning.

Specificaties

ISBN13:9783031653872
Taal:Engels
Bindwijze:gebonden
Aantal pagina's:150
Uitgever:Springer Nature Switzerland

Inhoudsopgave

<p>Background and Overview.- Entropy and Mutual Information.- Differential Entropy, Entropy Rate, and Maximum Entropy.- Typical Sequences and The AEP.- Markov Chains and Cascaded Systems.- Hypothesis Testing, Estimation, Information, and Sufficient Statistics.- Information Theoretic Quantities and Learning.- Estimation and Entropy Power.- Time Series Analyses.- Information Bottleneck Principle.- Channel Capacity.- Rate Distortion Theory.</p>
€ 60,99
Levertijd ongeveer 9 werkdagen
Gratis verzonden

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        Information Theoretic Principles for Agent Learning