On kernels, margins, and low-dimensional mappings

Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)

Volumn 3244, Issue , 2004, Pages 194-205

  Balcan, Maria Florina ^a   Blum, Avrim ^a   Vempala, Santosh ^b  

^a Carnegie Mellon University   (United States)

^b MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER SIMULATION; ERROR ANALYSIS; FUNCTIONS; LEARNING ALGORITHMS; MAPPING; POLYNOMIALS; PROBABILITY; THEOREM PROVING; ARTIFICIAL INTELLIGENCE; COMPUTERS;

KERNEL FUNCTION; LEARNING THEORY; POLYNOMIAL KERNEL; UNDERLYING DISTRIBUTION; HIGH DIMENSIONAL SPACES; JOHNSON-LINDENSTRAUSS LEMMATA; LINEARLY SEPARABLE; LOW-DIMENSIONAL SPACES; POLYNOMIAL KERNELS; STANDARD KERNELS;

LEARNING SYSTEMS; MAPPING;

EID: 22944491769     PISSN: 03029743     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/978-3-540-30215-5_16     Document Type: Conference Paper

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