This paper studies issues relating to the parameterization of probability distributions over binary data sets. Several such parameterizations of models for binary data are known, ...
David Buchman, Mark W. Schmidt, Shakir Mohamed, Da...
Existing Recurrent Neural Networks (RNNs) are limited in their ability to model dynamical systems with nonlinearities and hidden internal states. Here we use our general framework...
Many real-world data are maintained in relational format, with different tables storing information about entities and their links or relationships. The structure (schema) of the ...
Oliver Schulte, Hassan Khosravi, Flavia Moser, Mar...
Single inheritance often forces developers to duplicate code and logic. This widely recognized situation affects both business code and tests. In a large and complex application w...
In recent years, large databases of natural images have
become increasingly popular in the evaluation of face and
object recognition algorithms. However, Pinto et al. previously
...