We provide machine-independent characterizations of some complexity classes, over an arbitrary structure, in the model of computation proposed by L. Blum, M. Shub and S. Smale. We ...
Olivier Bournez, Felipe Cucker, Paulin Jacob&eacut...
We provide machine-independent characterizations of some complexity classes, over an arbitrary structure, in the model of computation proposed by L. Blum, M. Shub and S. Smale. We...
Olivier Bournez, Felipe Cucker, Paulin Jacob&eacut...
This paper presents the Topic-Aspect Model (TAM), a Bayesian mixture model which jointly discovers topics and aspects. We broadly define an aspect of a document as a characteristi...
The main aim of the work presented here is to contribute to computer science advances in the multimodal usability area, in-as-much as it addresses one of the major issues relating...
We characterize the size and complexity of the mammalian cortices of human, macaque, cat, rat, and mouse. We map the cortical structure onto a Bayesian confidence propagating neura...