Montreal / New York / Manchester / Pittsburgh / Vancouver / Cambridge / /
Company
Neural Information Processing Systems / MIT Press / Manchester University Press / Computer Laboratory / Microsoft / /
Country
Jordan / United States / Canada / United Kingdom / /
Facility
University of Cambridge / Computer Science University of Pittsburgh Pittsburgh / Large-Scale Transition Matrix Approximation Saeed Amizadeh Intelligent Systems Program University of Pittsburgh Pittsburgh / /
IndustryTerm
serial algorithm / multiplication algorithm / dynamical systems / recursive algorithm / orthogonal search tree / greedy algorithm / Linear-time algorithms / closed form solution / computing / similarity-graph based learning algorithms / /
MarketIndex
SLL / /
Organization
National Institute of Health / Large-Scale Transition Matrix Approximation Saeed Amizadeh Intelligent Systems Program University of Pittsburgh Pittsburgh / MIT / Computer Science University of Pittsburgh Pittsburgh / University of Cambridge / US Federal Reserve / Milos Hauskrecht Department / Pattern Analysis and Machine Intelligence / /
Person
D. Zhou / Alexander G. Gray / Jason Weston / Saeed Amizadeh / O. Bousquet / Bt / Bernhard Sch¨olkopf / Ram / T. Navin Lal / / /
Product
VariationalDT / Jensen / /
ProgrammingLanguage
Pascal / /
ProvinceOrState
Quebec / British Columbia / New York / Washington / Pennsylvania / Massachusetts / /
PublishedMedium
Machine Learning / Journal of Machine Learning Research / /
Technology
alpha / LP algorithm / Linear-time algorithms / serial algorithm / machine learning / SSL / recursive algorithm / SSL algorithm / similarity-graph based learning algorithms / multiplication algorithm / greedy algorithm / Variational DT algorithm / same algorithm / end function Algorithm / /
Variational Dual-Tree Framework for Large-Scale Transition Matrix Approximation Saeed Amizadeh Intelligent Systems Program University of Pittsburgh