Representation Discovery Using Harmonic Analysis

Author/creator Mahadevan, Sridhar Author
Other author Brachman, Ronald Contribution by
Other author Dietterich, Thomas Contribution by
Format Electronic
Publication InfoSan Rafael : Morgan & Claypool Publishers Williston : American International Distribution Corporation [Distributor]
Description147 p. 09.250 x 07.500 in.
Supplemental ContentFull text available from Computer & Information Science Collection One
Subjects

SeriesSynthesis Lectures on Artificial Intelligence and Machine Learning Ser.
Summary Annotation "This book is devoted to the problem of representation discovery: how can an intelligent system construct representations from its experience? Representation discovery re-parameterizes the state space - prior to the application of information retrieval, machine learning, or optimization techniques - facilitating later inference processes by constructing new task-specific bases adapted to the state space geometry. This book presents a general approach to representation discovery using the framework of harmonic analysis, in particular Fourier and wavelet analysis. A central goal of this book is to show that these analytical tools can be generalized from their usual setting in (infinite-dimensional) Euclidean spaces to discrete (finite-dimensional) spaces typically studied in many subfields of AI. Representation discovery is an actively developing field, and the author hopes this book will encourage other researchers into exploring this exciting area of research."--BOOK JACKET.
Access restrictionAvailable only to authorized users.
Technical detailsMode of access: World Wide Web
Genre/formElectronic books.
ISBN9781598296594
ISBN1598296590 (Trade Paper) Active Record
Standard identifier# 9781598296594
Stock number01307586

Availability

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Electronic Resources Access Content Online ✔ Available