1900 search results - page 215 / 380 » Gaussian Processes in Machine Learning |
86
Voted
ICML
2008
IEEE
16 years 1 months ago
2008
IEEE
The hierarchical Dirichlet process hidden Markov model (HDP-HMM) is a flexible, nonparametric model which allows state spaces of unknown size to be learned from data. We demonstra...
99
Voted
ECML
2007
Springer
15 years 6 months ago
2007
Springer
We present Policy Gradient Actor-Critic (PGAC), a new model-free Reinforcement Learning (RL) method for creating limited-memory stochastic policies for Partially Observable Markov ...
114
Voted
BMCBI
2010
15 years 17 days ago
2010
Background: This paper introduces the notion of optimizing different norms in the dual problem of support vector machines with multiple kernels. The selection of norms yields diff...
ICPR
2008
IEEE
16 years 1 months ago
2008
IEEE
This paper deals with pattern rejection strategies for self-paced Brain-Computer Interfaces (BCI). First, it introduces two pattern rejection strategies not used yet for self-pace...
106
Voted
ECML
2005
Springer
15 years 6 months ago
2005
Springer
Abstract. In this paper we consider latent variable models and introduce a new U-likelihood concept for estimating the distribution over hidden variables. One can derive an estimat...