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Bandit algorithms / (Record no. 103924)

MARC details
000 -LEADER
fixed length control field 03751cam a22004218i 4500
001 - CONTROL NUMBER
control field 21440656
003 - CONTROL NUMBER IDENTIFIER
control field BD-ChCU
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240324102125.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 200208s2020 enk b 001 0 eng
010 ## - LIBRARY OF CONGRESS CONTROL NUMBER
LC control number 2019053276
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781108486828
Qualifying information (hardback)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
Canceled/invalid ISBN 9781108571401
Qualifying information (epub)
040 ## - CATALOGING SOURCE
Original cataloging agency LBSOR/DLC
Language of cataloging eng
Description conventions rda
Transcribing agency DLC
042 ## - AUTHENTICATION CODE
Authentication code pcc
050 00 - LIBRARY OF CONGRESS CALL NUMBER
Classification number QA402.5
Item number .L367 2020
082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 519.3 L351 b
Edition number 23
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Lattimore, Tor,
Dates associated with a name 1987-
Relator term author.
245 10 - TITLE STATEMENT
Title Bandit algorithms /
Statement of responsibility, etc. Tor Lattimore and Csaba Szepesvari.
263 ## - PROJECTED PUBLICATION DATE
Projected publication date 2005
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture Cambridge ;
-- New York, NY :
Name of producer, publisher, distributor, manufacturer Cambridge University Press,
Date of production, publication, distribution, manufacture, or copyright notice 2020.
300 ## - PHYSICAL DESCRIPTION
Extent pages cm
336 ## - CONTENT TYPE
Content type term text
Content type code txt
Source rdacontent
337 ## - MEDIA TYPE
Media type term unmediated
Media type code n
Source rdamedia
338 ## - CARRIER TYPE
Carrier type term volume
Carrier type code nc
Source rdacarrier
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc. note Includes bibliographical references and index.
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Foundations of probability -- Stochastic processes and Markov chains -- Stochastic bandits -- Concentration of measure -- The explore-then-commit algorithm -- The upper confidence bound algorithm -- The upper confidence bound algorithm: asymptotic optimality -- The upper confidence bound algorithm: minimax optimality -- The upper confidence bound algorithm: Bernoulli noise -- The Exp3 algorithm -- The Exp3-IX algorithm -- Lower bounds: basic ideas -- Foundations of information theory -- Minimax lower bounds -- Instance dependent lower bounds -- High probability lower bounds -- Contextual bandits -- Stochastic linear bandits -- Confidence bounds for least squares estimators -- Optimal design for least squares estimators -- Stochastic linear bandits with finitely many arms -- Stochastic linear bandits with sparsity -- Minimax lower bounds for stochastic linear bandits -- Asymptotic lower bounds for stochastic linear bandits -- Foundations of convex analysis -- Exp3 for adversarial linear bandits -- Follow the regularized leader and mirror descent -- The relation between adversarial and stochastic linear bandits -- Combinatorial bandits -- Non-stationary bandits -- Ranking -- Pure exploration -- Foundations of Bayesian learning -- Bayesian bandits -- Thompson sampling -- Partial monitoring -- Markov decision processes.
520 ## - SUMMARY, ETC.
Summary, etc. "Decision-making in the face of uncertainty is a significant challenge in machine learning, and the multi-armed bandit model is a commonly used framework to address it. This comprehensive and rigorous introduction to the multi-armed bandit problem examines all the major settings, including stochastic, adversarial, and Bayesian frameworks. A focus on both mathematical intuition and carefully worked proofs makes this an excellent reference for established researchers and a helpful resource for graduate students in computer science, engineering, statistics, applied mathematics and economics. Linear bandits receive special attention as one of the most useful models in applications, while other chapters are dedicated to combinatorial bandits, ranking, non-stationary problems, Thompson sampling and pure exploration. The book ends with a peek into the world beyond bandits with an introduction to partial monitoring and learning in Markov decision processes"--
Assigning source Provided by publisher.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Mathematical optimization.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Probabilities.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Decision making
General subdivision Mathematical models.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Resource allocation
General subdivision Mathematical models.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Algorithms.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Szepesvári, Csaba,
Relator term author.
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Relationship information Online version:
Main entry heading Lattimore, Tor, 1987-
Title Bandit algorithms
Place, publisher, and date of publication Cambridge ; New York, NY : Cambridge University Press, 2020
International Standard Book Number 9781108571401
Record control number (DLC) 2019053277
906 ## - LOCAL DATA ELEMENT F, LDF (RLIN)
a 7
b cbc
c orignew
d 1
e ecip
f 20
g y-gencatlg
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Koha item type Books
Suppress in OPAC No
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Home library Current library Date acquired Total Checkouts Full call number Barcode Date last seen Copy number Price effective from Koha item type
    Dewey Decimal Classification     Chittagong University Library Chittagong University Library 03/24/2024   519.3 L351 b 329579 03/24/2024 c-1 03/24/2024 Books
    Dewey Decimal Classification     Chittagong University Library Chittagong University Library 03/24/2024   519.3 L351 b 329580 03/24/2024 C-2 03/24/2024 Books
    Dewey Decimal Classification     Chittagong University Library Chittagong University Library 03/24/2024   519.3 L351 b 329641 03/24/2024 C-3 03/24/2024 Books
    Dewey Decimal Classification     Chittagong University Library Chittagong University Library 03/24/2024   519.3 L351 b 329642 03/24/2024 C-4 03/24/2024 Books
    Dewey Decimal Classification     Chittagong University Library Chittagong University Library 03/24/2024   519.3 L351 b 329643 03/24/2024 C-5 03/24/2024 Books
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