We suggest improvements to a previously proposed framework for integrating Conditional Random Fields and Hidden Markov Models, dubbed a Crandem system (2009). The previous authors...
Rohit Prabhavalkar, Preethi Jyothi, William Hartma...
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...