We present a new evaluation criterion for the induction of decision trees. We exploit a parameter-free Bayesian approach and propose an analytic formula for the evaluation of the p...
This work addresses what we believe to be a central issue in the field of XML diff and merge computation: the mathematical modeling o-called editing deltas and the study of their ...
Update of acoustic and language models is vital to maintain performance of automatic speech recognition (ASR) systems. To alleviate efforts for updating models, we propose a "...
Yuya Akita, Masato Mimura, Graham Neubig, Tatsuya ...
Principal component analysis (PCA) is a classical data analysis technique that finds linear transformations of data that retain the maximal amount of variance. We study a case whe...
This paper describes a Bayesian algorithm for rigid/non-rigid 2D visual object tracking based on sparse image features. The algorithm is inspired by the way human visual cortex se...