MARC details
000 -LEADER |
fixed length control field |
03165cam a2200409 i 4500 |
001 - CONTROL NUMBER |
control field |
on1121203037 |
003 - CONTROL NUMBER IDENTIFIER |
control field |
OCoLC |
005 - DATE AND TIME OF LATEST TRANSACTION |
control field |
20240603105337.0 |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
fixed length control field |
190930t20192019maua b 001 0 eng d |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
International Standard Book Number |
9781733788502 |
Qualifying information |
(hardback) |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
International Standard Book Number |
1733788506 |
Qualifying information |
(hardback) |
029 1# - OTHER SYSTEM CONTROL NUMBER (OCLC) |
OCLC library identifier |
AU@ |
System control number |
000068352219 |
029 1# - OTHER SYSTEM CONTROL NUMBER (OCLC) |
OCLC library identifier |
DKDLA |
System control number |
820030-katalog:2566916 |
029 1# - OTHER SYSTEM CONTROL NUMBER (OCLC) |
OCLC library identifier |
ZWZ |
System control number |
256780560 |
035 ## - SYSTEM CONTROL NUMBER |
System control number |
(OCoLC)1121203037 |
Canceled/invalid control number |
(OCoLC)1122748297 |
040 ## - CATALOGING SOURCE |
Original cataloging agency |
MYG |
Language of cataloging |
eng |
Description conventions |
rda |
Transcribing agency |
MYG |
Modifying agency |
YDX |
-- |
OCLCF |
-- |
DGW |
-- |
OCLCO |
-- |
OCLCQ |
-- |
OCLCO |
-- |
NGU |
-- |
OCLCL |
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
Classification number |
519.72 |
Item number |
B551m |
100 1# - MAIN ENTRY--PERSONAL NAME |
Personal name |
Bertsimas, Dimitris, |
Relator term |
author. |
245 10 - TITLE STATEMENT |
Title |
Machine learning under a modern optimization lens / |
Statement of responsibility, etc. |
Dimitris Bertsimas, Jack Dunn. |
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
Place of production, publication, distribution, manufacture |
Belmont, Massachusetts : |
Name of producer, publisher, distributor, manufacturer |
Dynamic Ideas LLC, |
Date of production, publication, distribution, manufacture, or copyright notice |
[2019] |
264 #4 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
Date of production, publication, distribution, manufacture, or copyright notice |
©2019 |
300 ## - PHYSICAL DESCRIPTION |
Extent |
xviii, 589 pages : |
Other physical details |
color illustrations ; |
Dimensions |
24 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. |
520 ## - SUMMARY, ETC. |
Summary, etc. |
"The book provides an original treatment of machine learning (ML) using convex, robust and mixed integer optimization that leads to solutions to central ML problems at large scale that can be found in seconds/minutes, can be certified to be optimal in minutes/hours, and outperform classical heuristic approaches in out-of-sample experiments. Structure of the book: Part I covers robust, sparse, nonlinear, holistic regression and extensions. Part II contains optimal classification and regression trees. Part III outlines prescriptive ML methods. Part IV shows the power of optimization over randomization in design of experiments, exceptional responders, stable regression and the bootstrap. Part V describes unsupervised methods in ML: optimal missing data imputation and interpretable clustering. Part VI develops matrix ML methods: sparse PCA, sparse inverse covariance estimation, factor analysis, matrix and tensor completion. Part VII demonstrates how ML leads to interpretable optimization. Philosophical principles of the book: Interpretability in ML is materially important in real world applications. Practical tractability not polynomial solvability leads to real world impact. NP-hardness is an opportunity not an obstacle. ML is inherently linked to optimization not probability theory. Data represents an objective reality; models only exist in our imagination. Optimization has a significant edge over randomization. The ultimate objective in the real world is prescription, not prediction."--Cover. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name entry element |
Machine learning. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name entry element |
Mathematical optimization. |
650 #6 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name entry element |
Apprentissage automatique. |
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name entry element |
Machine learning. |
Source of heading or term |
fast |
Authority record control number or standard number |
(OCoLC)fst01004795 |
700 1# - ADDED ENTRY--PERSONAL NAME |
Personal name |
Dunn, Jack |
Fuller form of name |
(Jack William), |
Relator term |
author. |
Real World Object URI |
https://id.oclc.org/worldcat/entity/E39PCjHHmYqbMjRCxmdFfwwBKb |
758 ## - RESOURCE IDENTIFIER |
Relationship information |
has work: |
Label |
Machine learning under a modern optimization lens (Text) |
Real World Object URI |
https://id.oclc.org/worldcat/entity/E39PCGmxW6j6F4C6qTkx7xPPHy |
Relationship |
https://id.oclc.org/worldcat/ontology/hasWork |
942 ## - ADDED ENTRY ELEMENTS (KOHA) |
Source of classification or shelving scheme |
Dewey Decimal Classification |
Koha item type |
Books |
Suppress in OPAC |
No |
948 ## - LOCAL PROCESSING INFORMATION (OCLC); SERIES PART DESIGNATOR (RLIN) |
h (OCLC) |
NO HOLDINGS IN P5A - 41 OTHER HOLDINGS |