UAI
2001
13 years 5 months ago
2001
A serious problem in learning probabilistic models is the presence of hidden variables. These variables are not observed, yet interact with several of the observed variables. Dete...
NIPS
2007
13 years 6 months ago
2007
The learning of probabilistic models with many hidden variables and nondecomposable dependencies is an important and challenging problem. In contrast to traditional approaches bas...
NIPS
2007
13 years 6 months ago
2007
We investigate a new, convex relaxation of an expectation-maximization (EM) variant that approximates a standard objective while eliminating local minima. First, a cautionary resu...
PKDD
2009
Springer
13 years 9 months ago
2009
Springer
Monitoring the variables of real world dynamic systems is a difficult task due to their inherent complexity and uncertainty. Particle Filters (PF) perform that task, yielding prob...
ICML
2004
IEEE
13 years 10 months ago
2004
IEEE
We introduce a new perceptron-based discriminative learning algorithm for labeling structured data such as sequences, trees, and graphs. Since it is fully kernelized and uses poin...
ECML
2005
Springer
13 years 10 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...
ICASSP
2008
IEEE
13 years 11 months ago
2008
IEEE
Conditional Random Fields (CRFs) are often estimated using an entropy based criterion in combination with Generalized Iterative Scaling (GIS). GIS offers, upon others, the immedi...
ICASSP
2008
IEEE
13 years 11 months ago
2008
IEEE
We consider the problem of learning multiscale graphical models. Given a collection of variables along with covariance specifications for these variables, we introduce hidden var...
ICML
2005
IEEE
14 years 5 months ago
2005
IEEE
Learning the structure of graphical models is an important task, but one of considerable difficulty when latent variables are involved. Because conditional independences using hid...