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AROBOTS
2002
115views more  AROBOTS 2002»
15 years 4 months ago
Statistical Learning for Humanoid Robots
The complexity of the kinematic and dynamic structure of humanoid robots make conventional analytical approaches to control increasingly unsuitable for such systems. Learning techn...
Sethu Vijayakumar, Aaron D'Souza, Tomohiro Shibata...
ESANN
2004
15 years 6 months ago
Self-organizing context learning
This work is designed to contribute to a deeper understanding of the recently proposed Merging SOM (MSOM). Its context model aims at the representation of sequences, an important s...
Marc Strickert, Barbara Hammer
157
Voted
SDM
2004
SIAM
218views Data Mining» more  SDM 2004»
15 years 6 months ago
Mixture Density Mercer Kernels: A Method to Learn Kernels Directly from Data
This paper presents a method of generating Mercer Kernels from an ensemble of probabilistic mixture models, where each mixture model is generated from a Bayesian mixture density e...
Ashok N. Srivastava
126
Voted
INTERSPEECH
2010
14 years 11 months ago
Online adaptive learning for speech recognition decoding
We describe a new method for pruning in dynamic models based on running an adaptive filtering algorithm online during decoding to predict aspects of the scores in the near future....
Jeff Bilmes, Hui Lin
119
Voted
JMLR
2010
88views more  JMLR 2010»
14 years 11 months ago
Inference and Learning in Networks of Queues
Probabilistic models of the performance of computer systems are useful both for predicting system performance in new conditions, and for diagnosing past performance problems. The ...
Charles A. Sutton, Michael I. Jordan