598 search results - page 49 / 120 » Learning Generative Models with the Up-Propagation Algorithm |
75
Voted
CVPR
2003
IEEE
15 years 11 months ago
2003
IEEE
By mapping a set of input images to points in a lowdimensional manifold or subspace, it is possible to efficiently account for a small number of degrees of freedom. For example, i...
ICML
2007
IEEE
15 years 10 months ago
2007
IEEE
Markov logic networks (MLNs) are a statistical relational model that consists of weighted firstorder clauses and generalizes first-order logic and Markov networks. The current sta...
83
Voted
ICML
2010
IEEE
14 years 10 months ago
2010
IEEE
Deep Belief Networks (DBNs) are hierarchical generative models which have been used successfully to model high dimensional visual data. However, they are not robust to common vari...
NIPS
2007
14 years 11 months ago
2007
We show how to use unlabeled data and a deep belief net (DBN) to learn a good covariance kernel for a Gaussian process. We first learn a deep generative model of the unlabeled da...
MOBISYS
2007
ACM
15 years 9 months ago
2007
ACM
An algorithm has been developed to automatically construct individual models of normal activity within a home using motion sensor data. Alerts can be generated when a period of in...