JMLR
2010
13 years 5 months ago
2010
We present a new approximate inference algorithm for Deep Boltzmann Machines (DBM's), a generative model with many layers of hidden variables. The algorithm learns a separate...
IJAR
2006
13 years 11 months ago
2006
Although influence diagrams are powerful tools for representing and solving complex decisionmaking problems, their evaluation may require an enormous computational effort and this...
NIPS
1998
14 years 10 days ago
1998
Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
SIGMOD
2010
ACM
14 years 3 months ago
2010
ACM
Real-world databases often contain syntactic and semantic errors, in spite of integrity constraints and other safety measures incorporated into modern DBMSs. We present ERACER, an...
AIME
2007
Springer
14 years 5 months ago
2007
Springer
Abstract. In the current paper, the Promedas model for internal medicine, developed by our team, is introduced. The model is based on up-todate medical knowledge and consists of ap...
CVPR
2010
IEEE
14 years 7 months ago
2010
IEEE
Maximum a posteriori (MAP) inference in Markov Random Fields (MRFs) is an NP-hard problem, and thus research has focussed on either finding efficiently solvable subclasses (e.g. t...