Information-theoretic lower bounds on the oracle complexity of convex optimization

Advances in Neural Information Processing Systems 22 - Proceedings of the 2009 Conference

Volumn , Issue , 2009, Pages 1-9

  Agarwal, Alekh ^a   Bartlett, Peter ^a   Ravikumar, Pradeep ^b   Wainwright, Martin J ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b UNIVERSITY OF TEXAS AT AUSTIN   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

INFORMATION THEORY; LEARNING SYSTEMS; STOCHASTIC MODELS; STOCHASTIC SYSTEMS;

COMPLEXITY ESTIMATES; CONVEX OPTIMISATION; INFORMATION-THEORETIC LOWER BOUNDS; MACHINE-LEARNING; MINIMAX; MODEL OF COMPUTATION; ORACLE MODEL; STOCHASTICS; UPPER BOUND; VARIOUS FUNCTIONS;

CONVEX OPTIMIZATION;

EID: 80053968588     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (11)

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