OPTIMAL COMPUTATIONAL AND STATISTICAL RATES OF CONVERGENCE FOR SPARSE NONCONVEX LEARNING PROBLEMS
OPTIMAL COMPUTATIONAL AND STATISTICAL RATES OF CONVERGENCE FOR SPARSE NONCONVEX LEARNING PROBLEMS
About this item
Full title
Author / Creator
Wang, Zhaoran , Liu, Han and Zhang, Tong
Publisher
United States: Institute of Mathematical Statistics
Journal title
Language
English
Formats
Publication information
Publisher
United States: Institute of Mathematical Statistics
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More information
Scope and Contents
Contents
We provide theoretical analysis of the statistical and computational properties of penalized M-estimators that can be formulated as the solution to a possibly nonconvex optimization problem. Many important estimators fall in this category, including least squares regression with nonconvex regularization, generalized linear models with nonconvex reg...
Alternative Titles
Full title
OPTIMAL COMPUTATIONAL AND STATISTICAL RATES OF CONVERGENCE FOR SPARSE NONCONVEX LEARNING PROBLEMS
Authors, Artists and Contributors
Author / Creator
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Primary Identifiers
Record Identifier
TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_4276088
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_4276088
Other Identifiers
ISSN
0090-5364
E-ISSN
2168-8966
DOI
10.1214/14-aos1238
