First-order and stochastic optimization methods for machine learning (Record no. 4503)

MARC details
000 -LEADER
fixed length control field 01845nam a2200289Ia 4500
003 - CONTROL NUMBER IDENTIFIER
control field OSt
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20251117124121.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 220909b |||||||| |||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783030395674
037 ## - SOURCE OF ACQUISITION
Terms of availability Textual
040 ## - CATALOGING SOURCE
Language of cataloging eng
Original cataloging agency CSL
Transcribing agency CSL
Modifying agency CSL
041 ## - LANGUAGE CODE
Language code of text/sound track or separate title eng
084 ## - COLON CLASSIFICATION NUMBER
Classification number B2811093 R0
Assigning agency CSL
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Lan, Guanghui
Relator term author
9 (RLIN) 851646
245 #0 - TITLE STATEMENT
Title First-order and stochastic optimization methods for machine learning
Statement of responsibility, etc. / by Lan Guanghui
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. Switzerland,
Name of publisher, distributor, etc. Springer:
Date of publication, distribution, etc. 2020
300 ## - PHYSICAL DESCRIPTION
Extent xiii, 582p.
Other physical details : ill.
490 ## - SERIES STATEMENT
Series statement Springer series in the data sciences
International Standard Serial Number 2365-5674
500 ## - GENERAL NOTE
General note References 567-575p.; Index 577-582p.
520 ## - SUMMARY, ETC.
Summary, etc. This book covers not only foundational materials but also the most recent progresses made during the past few years on the area of machine learning algorithms. In spite of the intensive research and development in this area, there does not exist a systematic treatment to introduce the fundamental concepts and recent progresses on machine learning algorithms, especially on those based on stochastic optimization methods, randomized algorithms, nonconvex optimization, distributed and online learning, and projection free methods. This book will benefit the broad audience in the area of machine learning, artificial intelligence and mathematical programming community by presenting these recent developments in a tutorial style, starting from the basic building blocks to the most carefully designed and complicated algorithms for machine learning.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Machine learning models
9 (RLIN) 851647
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Noncovex optimization
9 (RLIN) 851648
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Stochastic convex optimization
9 (RLIN) 851649
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Operational Research
9 (RLIN) 851650
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Classification part B2811093 R0
Koha item type Textual
Source of classification or shelving scheme Colon Classification (CC)
Suppress in OPAC No
Holdings
Withdrawn status Lost status Damaged status Not for loan Home library Current library Date acquired Source of acquisition Total Checkouts Full call number Barcode Date last seen Price effective from Koha item type
        Central Science Library Central Science Library 2022-09-12 1871, 14/12/2021, Bright Book Service   B2811093 R0 SL1654757 2022-09-12 2022-09-12 Textual