99 search results - page 10 / 20 » Learning Hidden Markov Models with Distributed State Represe... |
ICML
2007
IEEE
14 years 8 months ago
2007
IEEE
A new hierarchical nonparametric Bayesian model is proposed for the problem of multitask learning (MTL) with sequential data. Sequential data are typically modeled with a hidden M...
INTERSPEECH
2010
13 years 2 months ago
2010
We investigate incremental word learning in a Hidden Markov Model (HMM) framework suitable for human-robot interaction. In interactive learning, the tutoring time is a crucial fac...
ILP
2007
Springer
14 years 1 months ago
2007
Springer
Abstract. Many reinforcement learning domains are highly relational. While traditional temporal-difference methods can be applied to these domains, they are limited in their capaci...
ICML
2005
IEEE
14 years 8 months ago
2005
IEEE
This paper explores the issue of recognizing, generalizing and reproducing arbitrary gestures. We aim at extracting a representation that encapsulates only the key aspects of the ...
ICML
2000
IEEE
14 years 8 months ago
2000
IEEE
Hidden Markov models (HMMs) are a powerful probabilistic tool for modeling sequential data, and have been applied with success to many text-related tasks, such as part-of-speech t...