147 search results - page 26 / 30 » Learning Multi-linear Representations of Distributions for E... |
111
Voted
JAIR
2006
15 years 1 months ago
2006
The most basic assumption used in statistical learning theory is that training data and test data are drawn from the same underlying distribution. Unfortunately, in many applicati...
101
Voted
ICONIP
2004
15 years 2 months ago
2004
Variational methods have proved popular and effective for inference and learning in intractable graphical models. An attractive feature of the approaches based on the Kullback-Lei...
131
Voted
ICCV
2009
IEEE
14 years 11 months ago
2009
IEEE
This paper examines the problem of moving object detection. More precisely, it addresses the difficult scenarios where background scene textures in the video might change over tim...
145
Voted
CSDA
2007
15 years 21 days ago
2007
In blind source separation, there are M sources that produce sounds independently and continuously over time. These sounds are then recorded by m receivers. The sound recorded by ...
124
Voted
KDD
2009
ACM
16 years 1 months ago
2009
ACM
Learning probabilistic graphical models from high-dimensional datasets is a computationally challenging task. In many interesting applications, the domain dimensionality is such a...