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IJCAI
2003
14 years 11 months ago
When Discriminative Learning of Bayesian Network Parameters Is Easy
Bayesian network models are widely used for discriminative prediction tasks such as classification. Usually their parameters are determined using 'unsupervised' methods ...
Hannes Wettig, Peter Grünwald, Teemu Roos, Pe...
AGI
2008
14 years 11 months ago
Artificial General Intelligence through Large-Scale, Multimodal Bayesian Learning
Abstract. An artificial system that achieves human-level performance on opendomain tasks must have a huge amount of knowledge about the world. We argue that the most feasible way t...
Brian Milch
VISAPP
2010
14 years 8 months ago
Inverse Problems in Imaging and Computer Vision - From Regularization Theory to Bayesian Inference
phies are also mentioned and a common mathematical abstraction for all these inverses problems will be presented. By focusing on a simple linear forward model, first a synthetic an...
Ali Mohammad-Djafari
AIME
2007
Springer
15 years 2 months ago
Using Temporal Context-Specific Independence Information in the Exploratory Analysis of Disease Processes
Abstract. Disease processes in patients are temporal in nature and involve uncertainty. It is necessary to gain insight into these processes when aiming at improving the diagnosis,...
Stefan Visscher, Peter J. F. Lucas, Ildikó ...
ICDM
2009
IEEE
132views Data Mining» more  ICDM 2009»
15 years 4 months ago
Bayesian Overlapping Subspace Clustering
Given a data matrix, the problem of finding dense/uniform sub-blocks in the matrix is becoming important in several applications. The problem is inherently combinatorial since th...
Qiang Fu, Arindam Banerjee