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» Learning the Structure of Dynamic Probabilistic Networks
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NIPS
2000
13 years 9 months ago
Discovering Hidden Variables: A Structure-Based Approach
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. As s...
Gal Elidan, Noam Lotner, Nir Friedman, Daphne Koll...
AAI
2002
109views more  AAI 2002»
13 years 7 months ago
Probabilistic Assessment of User's Emotions in Educational Games
We present a probabilistic model to monitor a user's emotions and engagement during the interaction with educational games. We illustrate how our probabilistic model assesses...
Cristina Conati
APIN
1999
107views more  APIN 1999»
13 years 7 months ago
Massively Parallel Probabilistic Reasoning with Boltzmann Machines
We present a method for mapping a given Bayesian network to a Boltzmann machine architecture, in the sense that the the updating process of the resulting Boltzmann machine model pr...
Petri Myllymäki
SOCIALCOM
2010
13 years 5 months ago
Using Text Analysis to Understand the Structure and Dynamics of the World Wide Web as a Multi-Relational Graph
A representation of the World Wide Web as a directed graph, with vertices representing web pages and edges representing hypertext links, underpins the algorithms used by web search...
Harish Sethu, Alexander Yates
JMLR
2000
134views more  JMLR 2000»
13 years 7 months ago
Learning with Mixtures of Trees
This paper describes the mixtures-of-trees model, a probabilistic model for discrete multidimensional domains. Mixtures-of-trees generalize the probabilistic trees of Chow and Liu...
Marina Meila, Michael I. Jordan