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Optimization algorithms for distributed machine learning (Record no. 567635)

MARC details
000 -LEADER
fixed length control field 01443 a2200217 4500
003 - CONTROL NUMBER IDENTIFIER
control field OSt
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20250910123601.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 250910b |||||||| |||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9783031190667
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.31
Item number J837o
100 ## - MAIN ENTRY--AUTHOR NAME
Personal name Joshi, Gauri
245 ## - TITLE STATEMENT
Title Optimization algorithms for distributed machine learning
Statement of responsibility, etc Gauri Joshi
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Name of publisher Springer
Year of publication 2023
Place of publication Switzerland
300 ## - PHYSICAL DESCRIPTION
Number of Pages xiii, 127p
440 ## - SERIES STATEMENT/ADDED ENTRY--TITLE
Title Synthesis lectures on learning, networks, and algorithms
490 ## - SERIES STATEMENT
Series statement / edited by Lei Ying
520 ## - SUMMARY, ETC.
Summary, etc This book discusses state-of-the-art stochastic optimization algorithms for distributed machine learning and analyzes their convergence speed. The book first introduces stochastic gradient descent (SGD) and its distributed version, synchronous SGD, where the task of computing gradients is divided across several worker nodes. The author discusses several algorithms that improve the scalability and communication efficiency of synchronous SGD, such as asynchronous SGD, local-update SGD, quantized and sparsified SGD, and decentralized SGD. For each of these algorithms, the book analyzes its error versus iterations convergence, and the runtime spent per iteration. The author shows that each of these strategies to reduce communication or synchronization delays encounters a fundamental trade-off between error and runtime.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical Term Computer algorithms
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical Term Machine learning
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type Reference
Holdings
Withdrawn status Lost status Damaged status Not for loan Collection code Home library Current library Date acquired Source of acquisition Cost, normal purchase price Full call number Accession Number Cost, replacement price Koha item type
        In Acquisition PK Kelkar Library, IIT Kanpur PK Kelkar Library, IIT Kanpur 10/09/2025 2 3442.75 006.31 J78o A187031 4590.33 Reference

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