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ICML
2010
IEEE
13 years 10 months ago
Learning Deep Boltzmann Machines using Adaptive MCMC
When modeling high-dimensional richly structured data, it is often the case that the distribution defined by the Deep Boltzmann Machine (DBM) has a rough energy landscape with man...
Ruslan Salakhutdinov
NAACL
2010
13 years 7 months ago
Inducing Synchronous Grammars with Slice Sampling
This paper describes an efficient sampler for synchronous grammar induction under a nonparametric Bayesian prior. Inspired by ideas from slice sampling, our sampler is able to dra...
Phil Blunsom, Trevor Cohn
COGSCI
2007
99views more  COGSCI 2007»
13 years 9 months ago
Language Evolution by Iterated Learning With Bayesian Agents
Languages are transmitted from person to person and generation to generation via a process of iterated learning: people learn a language from other people who once learned that la...
Thomas L. Griffiths, Michael L. Kalish
BMCBI
2006
175views more  BMCBI 2006»
13 years 9 months ago
Parameter estimation for stiff equations of biosystems using radial basis function networks
Background: The modeling of dynamic systems requires estimating kinetic parameters from experimentally measured time-courses. Conventional global optimization methods used for par...
Yoshiya Matsubara, Shinichi Kikuchi, Masahiro Sugi...
SDM
2012
SIAM
237views Data Mining» more  SDM 2012»
11 years 11 months ago
A Distributed Kernel Summation Framework for General-Dimension Machine Learning
Kernel summations are a ubiquitous key computational bottleneck in many data analysis methods. In this paper, we attempt to marry, for the first time, the best relevant technique...
Dongryeol Lee, Richard W. Vuduc, Alexander G. Gray