NIPS
2007
13 years 6 months ago
2007
The expectation maximization (EM) algorithm is a widely used maximum likelihood estimation procedure for statistical models when the values of some of the variables in the model a...
ESANN
2008
13 years 6 months ago
2008
In this paper, we propose a new methodology to build latent variables that are optimal if a nonlinear model is used afterward. This method is based on Nonparametric Noise Estimatio...
KDD
2010
ACM
13 years 9 months ago
2010
ACM
One of the important approaches for Knowledge discovery and Data mining is to estimate unobserved variables because latent variables can indicate hidden and specific properties o...
ECCV
2010
Springer
13 years 10 months ago
2010
Springer
Abstract. In this paper we propose a probabilistic framework that models shape variations and infers dense and detailed 3D shapes from a single silhouette. We model two types of sh...
ECCV
2010
Springer
13 years 10 months ago
2010
Springer
We address the problem of understanding an indoor scene from a single image in terms of recovering the layouts of the faces (floor, ceiling, walls) and furniture. A major challeng...
ICTAI
2005
IEEE
13 years 10 months ago
2005
IEEE
In this paper, we propose a novel stochastic framework for unsupervised manifold learning. The latent variables are introduced, and the latent processes are assumed to characteriz...
CVPR
2010
IEEE
13 years 10 months ago
2010
IEEE
We consider the problem of recognizing human actions from still images. We propose a novel approach that treats the pose of the person in the image as latent variables that will h...
CVPR
2010
IEEE
13 years 10 months ago
2010
IEEE
We present a latent hierarchical structural learning method for object detection. An object is represented by a mixture of hierarchical tree models where the nodes represent objec...
CRV
2008
IEEE
13 years 11 months ago
2008
IEEE
We propose a generative statistical approach to human motion modeling and tracking that utilizes probabilistic latent semantic (PLSA) models to describe the mapping of image featu...
ICTAI
2009
IEEE
13 years 11 months ago
2009
IEEE
Energy-based learning (EBL) is a general framework to describe supervised and unsupervised training methods for probabilistic and non-probabilistic factor graphs. An energy-based ...