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» Gaussian Processes in Machine Learning
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94
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ESANN
2008
15 years 1 months ago
Learning Inverse Dynamics: a Comparison
While it is well-known that model can enhance the control performance in terms of precision or energy efficiency, the practical application has often been limited by the complexiti...
Duy Nguyen-Tuong, Jan Peters, Matthias Seeger, Ber...
102
Voted
ML
2010
ACM
151views Machine Learning» more  ML 2010»
14 years 11 months ago
Inductive transfer for learning Bayesian networks
In several domains it is common to have data from different, but closely related problems. For instance, in manufacturing, many products follow the same industrial process but with...
Roger Luis, Luis Enrique Sucar, Eduardo F. Morales
77
Voted
PST
2004
15 years 1 months ago
Supporting Privacy in E-Learning with Semantic Streams
The goal of the semantic web is to facilitate the exchange of meaningful information in a form that is easy for machines to process. The goal of an e-learning system is to support ...
Lori Kettel, Christopher A. Brooks, Jim E. Greer
ICASSP
2011
IEEE
14 years 4 months ago
Improving melody extraction using Probabilistic Latent Component Analysis
We propose a new approach for automatic melody extraction from polyphonic audio, based on Probabilistic Latent Component Analysis (PLCA). An audio signal is first divided into vo...
Jinyu Han, Ching-Wei Chen
121
Voted
ICASSP
2011
IEEE
14 years 4 months ago
HNM-based MFCC+F0 extractor applied to statistical speech synthesis
Currently, the statistical framework based on Hidden Markov Models (HMMs) plays a relevant role in speech synthesis, while voice conversion systems based on Gaussian Mixture Model...
Daniel Erro, Iñaki Sainz, Eva Navas, Inma H...