The fundamental incompatibility of scalable hamiltonian monte carlo and naive data subsampling

32nd International Conference on Machine Learning, ICML 2015

Volumn 1, Issue , 2015, Pages 533-540

  Betancourt, Michael ^a  

^a UNIVERSITY OF WARWICK   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

APPROXIMATION ALGORITHMS; ARTIFICIAL INTELLIGENCE; LEARNING SYSTEMS; MONTE CARLO METHODS;

COMPUTATIONALLY EFFICIENT; DATA-INTENSIVE APPLICATION; HAMILTONIAN FLOWS; HIGH-DIMENSIONAL; MONTE CARLO ESTIMATORS;

HAMILTONIANS;

EID: 84969498066     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

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