Quantization of continuous variables is important in data analysis, especially for some model classes such as Bayesian networks and decision trees, which use discrete variables. Of...
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 present an algorithmic analog-to-digital converter (ADC) architecture for large-scale parallel quantization of internally analog variables in externally digital array processor...
Human-Machine interfaces play a role of growing importance as computer technology continues to evolve. Motivated by the desire to provide users with an intuitive gesture input syst...
We propose using simple mixture models to define a set of mid-level binary local features based on binary oriented edge input. The features capture natural local structures in the...