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NIPS
1996
15 years 29 days 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 11 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 10 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 8 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 6 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