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NIPS
1996
14 years 11 months ago
Continuous Sigmoidal Belief Networks Trained using Slice Sampling
Real-valued random hidden variables can be useful for modelling latent structure that explains correlations among observed variables. I propose a simple unit that adds zero-mean G...
Brendan J. Frey
JMLR
2006
138views more  JMLR 2006»
14 years 9 months ago
Noisy-OR Component Analysis and its Application to Link Analysis
We develop a new component analysis framework, the Noisy-Or Component Analyzer (NOCA), that targets high-dimensional binary data. NOCA is a probabilistic latent variable model tha...
Tomás Singliar, Milos Hauskrecht
SCP
2010
96views more  SCP 2010»
14 years 8 months ago
Enforcing structural regularities in software using IntensiVE
The design and implementation of a software system is often governed by a variety of coding conventions, design patterns, architectural guidelines, design rules, and other so-call...
Johan Brichau, Andy Kellens, Sergio Castro, Theo D...
ICCAD
2006
IEEE
99views Hardware» more  ICCAD 2006»
15 years 6 months ago
Variability and yield improvement: rules, models, and characterization
Yield and variability are becoming detractors for successful design in sub-90-nm process technologies. We consider the fundamental lithography and process issues that are driving ...
Kenneth L. Shepard, Daniel N. Maynard
JMLR
2010
143views more  JMLR 2010»
14 years 4 months ago
Incremental Sigmoid Belief Networks for Grammar Learning
We propose a class of Bayesian networks appropriate for structured prediction problems where the Bayesian network's model structure is a function of the predicted output stru...
James Henderson, Ivan Titov