ICWSM
2009
13 years 2 months ago
2009
The advent of social tagging systems has enabled a new community-based view of the Web in which objects like images, videos, and Web pages are annotated by thousands of users. Und...
CLEF
2009
Springer
13 years 5 months ago
2009
Springer
We present Promodes, an algorithm for unsupervised word decomposition, which is based on a probabilistic generative model. The model considers segment boundaries as hidden variable...
NIPS
2007
13 years 5 months ago
2007
We present a probabilistic generative model of visual attributes, together with an efficient learning algorithm. Attributes are visual qualities of objects, such as ‘red’, ...
EMNLP
2007
13 years 6 months ago
2007
In this paper, we proposed a novel probabilistic generative model to deal with explicit multiple-topic documents: Parametric Dirichlet Mixture Model(PDMM). PDMM is an expansion of...
CVPR
2010
IEEE
14 years 20 days ago
2010
IEEE
The dynamic texture (DT) is a probabilistic generative model, defined over space and time, that represents a video as the output of a linear dynamical system (LDS). The DT model ...
KDD
2007
ACM
14 years 4 months ago
2007
ACM
Documents, such as those seen on Wikipedia and Folksonomy, have tended to be assigned with multiple topics as a meta-data. Therefore, it is more and more important to analyze a re...
KDD
2008
ACM
2008
ACM
Knowledge discovery of semantic relationships between words using nonparametric bayesian graph model
14 years 4 months ago
We developed a model based on nonparametric Bayesian modeling for automatic discovery of semantic relationships between words taken from a corpus. It is aimed at discovering seman...
ICCV
2007
IEEE
14 years 6 months ago
2007
IEEE
We propose a simple probabilistic generative model for image segmentation. Like other probabilistic algorithms (such as EM on a Mixture of Gaussians) the proposed model is princip...
CVPR
2008
IEEE
14 years 6 months ago
2008
IEEE
In this paper, we present a novel on-line probabilistic generative model that simultaneously deals with both the clustering and the tracking of an unknown number of moving objects...