MARC details
| 000 -LEADER |
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| fixed length control field |
03378cam a2200373 i 4500 |
| 001 - CONTROL NUMBER |
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| control field |
21347946 |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20241204121046.0 |
| 006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS--GENERAL INFORMATION |
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| fixed length control field |
m |o d | |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION |
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| fixed length control field |
cr ||||||||||| |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
191215s2020 nju ob 001 0 eng |
| 010 ## - LIBRARY OF CONGRESS CONTROL NUMBER |
|---|
| LC control number |
2019048293 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9780691200316 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| Cancelled/invalid ISBN |
9780691197296 |
| 040 ## - CATALOGING SOURCE |
|---|
| Original cataloging agency |
DLC |
| Language of cataloging |
eng |
| Transcribing agency |
DLC |
| Description conventions |
rda |
| Modifying agency |
DLC |
| 042 ## - AUTHENTICATION CODE |
|---|
| Authentication code |
pcc |
| 050 00 - LIBRARY OF CONGRESS CALL NUMBER |
|---|
| Classification number |
QA276 |
| Item number |
.J83 2020 |
| 082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER |
|---|
| Classification number |
519.5/4 |
| Edition number |
23 |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Juditsky, Anatoli, |
| Dates associated with a name |
1962- |
| Relator term |
author. |
| 9 (RLIN) |
27350 |
| 245 10 - TITLE STATEMENT |
|---|
| Title |
Statistical inference via convex optimization / |
| Statement of responsibility, etc |
by Anatoli Juditsky, & Arkadi Nemirovski. |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
|---|
| Place of publication, distribution, etc |
New Jersey: |
| Name of publisher, distributor, etc |
Princeton University Press, |
| Date of publication, distribution, etc |
2020 |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xv,631p.: |
| Dimensions |
26 cm |
| 490 0# - SERIES STATEMENT |
|---|
| Series statement |
Princeton series in applied mathematics |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
|---|
| Bibliography, etc |
Includes bibliographical references and index. |
| 505 0# - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
On computational tractability -- Sparse recovery via ℓ₁ minimization -- Hypothesis testing -- From hypothesis testing to estimating functionals -- Signal recovery by linear estimation -- Signal recovery beyond linear estimates -- Solutions to selected exercises. |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc |
"This authoritative book draws on the latest research to explore the interplay of high-dimensional statistics with optimization. Through an accessible analysis of fundamental problems of hypothesis testing and signal recovery, Anatoli Juditsky and Arkadi Nemirovski show how convex optimization theory can be used to devise and analyze near-optimal statistical inferences. Statistical Inference via Convex Optimization is an essential resource for optimization specialists who are new to statistics and its applications, and for data scientists who want to improve their optimization methods. Juditsky and Nemirovski provide the first systematic treatment of the statistical techniques that have arisen from advances in the theory of optimization. They focus on four well-known statistical problems-sparse recovery, hypothesis testing, and recovery from indirect observations of both signals and functions of signals-demonstrating how they can be solved more efficiently as convex optimization problems. The emphasis throughout is on achieving the best possible statistical performance. The construction of inference routines and the quantification of their statistical performance are given by efficient computation rather than by analytical derivation typical of more conventional statistical approaches. In addition to being computation-friendly, the methods described in this book enable practitioners to handle numerous situations too difficult for closed analytical form analysis, such as composite hypothesis testing and signal recovery in inverse problems. Statistical Inference via Convex Optimization features exercises with solutions along with extensive appendixes, making it ideal for use as a graduate text"-- |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Mathematical statistics. |
| 9 (RLIN) |
890 |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Mathematical optimization. |
| 9 (RLIN) |
27351 |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Convex functions. |
| 9 (RLIN) |
27352 |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Nemirovskiĭ, A. S. |
| Fuller form of name |
(Arkadiĭ Semenovich), |
| Relator term |
author. |
| 9 (RLIN) |
27353 |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY |
|---|
| Display text |
Print version: |
| Main entry heading |
Juditsky, Anatoli, 1962- |
| Title |
Statistical inference via convex optimization |
| Place, publisher, and date of publication |
Princeton : Princeton University Press, [2020] |
| International Standard Book Number |
9780691197296 |
| Record control number |
(DLC) 2019048292 |
| 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 |
Library of Congress Classification |
| Item type |
Books |
| Classification part |
QA276 |
| Call number prefix |
QA276 |
| Call number suffix |
.J83 2020 |
