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» Phone recognition using Restricted Boltzmann Machines
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JMLR
2010
145views more  JMLR 2010»
13 years 2 months ago
Parallelizable Sampling of Markov Random Fields
Markov Random Fields (MRFs) are an important class of probabilistic models which are used for density estimation, classification, denoising, and for constructing Deep Belief Netwo...
James Martens, Ilya Sutskever
KDD
2010
ACM
265views Data Mining» more  KDD 2010»
13 years 11 months ago
Combining predictions for accurate recommender systems
We analyze the application of ensemble learning to recommender systems on the Netflix Prize dataset. For our analysis we use a set of diverse state-of-the-art collaborative filt...
Michael Jahrer, Andreas Töscher, Robert Legen...
ICPR
2010
IEEE
13 years 11 months ago
Deep Belief Networks for Real-Time Extraction of Tongue Contours from Ultrasound During Speech
Ultrasound has become a useful tool for speech scientists studying mechanisms of language sound production. State-of-the-art methods for extracting tongue contours from ultrasound...
Ian Fasel, Jeff Berry
ICDM
2009
IEEE
98views Data Mining» more  ICDM 2009»
14 years 2 months ago
Topic Distributions over Links on Web
—It is well known that Web users create links with different intentions. However, a key question, which is not well studied, is how to categorize the links and how to quantify th...
Jie Tang, Jing Zhang, Jeffrey Xu Yu, Zi Yang, Keke...
ICML
2008
IEEE
14 years 8 months ago
Modified MMI/MPE: a direct evaluation of the margin in speech recognition
In this paper we show how common speech recognition training criteria such as the Minimum Phone Error criterion or the Maximum Mutual Information criterion can be extended to inco...
Georg Heigold, Hermann Ney, Ralf Schlüter, Th...