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...
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...
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...
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 ...
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...