Information-theoretic framework for optimization with application to supervised learning

IEEE International Symposium on Information Theory - Proceedings

Volumn , Issue , 1995, Pages 257-

  Miller, David ^a   Rao, Ajit ^a   Rose, Kenneth ^a   Gersho, Allen ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION (OF INFORMATION); COMPUTATIONAL COMPLEXITY; DATA PROCESSING; ERRORS; GRAPH THEORY; LEARNING SYSTEMS; OPTIMIZATION; PROBABILITY; RANDOM PROCESSES; REGRESSION ANALYSIS; SIMULATED ANNEALING; VECTOR QUANTIZATION;

DATA CLUSTERING; DESCENT-BASED METHODS; INFORMATION-THEORETIC FRAMEWORK; PIECEWISE REGRESSION; SHANNON'S ENTROPY MEASURE; STATISTICAL CLASSIFIER; STATISTICAL PHYSICS; STOCHASTIC ANNEALING; SUPERVISED LEARNING;

INFORMATION THEORY;

EID: 0029179914     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (4)