We present several modifications of the original recurrent neural network language model (RNN LM). While this model has been shown to significantly outperform many competitive l...
Tomas Mikolov, Stefan Kombrink, Lukas Burget, Jan ...
Plagiarism detection has been considered as a classification problem which can be approximated with intrinsic strategies, considering self-based information from a given document,...
Gabriel Oberreuter, Gaston L'Huillier, Sebasti&aac...
Abstract Population-based meta-heuristics are algorithms that can obtain very good results for complex continuous optimization problems in a reduced amount of time. These search al...
Amilkar Puris, Rafael Bello, Daniel Molina, Franci...
We present SpeedBoost, a natural extension of functional gradient descent, for learning anytime predictors, which automatically trade computation time for predictive accuracy by s...
We present a method for space-time completion of large space-time "holes" in video sequences of complex dynamic scenes. The missing portions are filled-in by sampling sp...