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 ...
Given any generative classifier based on an inexact density model, we can define a discriminative counterpart that reduces its asymptotic error rate, while increasing the estima...
Using Shafer and Vovk's game-theoretic framework for probability, we derive a capital asset pricing model from an efficient market hypothesis, with no assumptions about the b...
Managing long verification error traces is one of the key challenges of automated debugging engines. Today, debuggers rely on the iterative logic array to model sequential behavior...
This paper provides an algorithmic framework for learning statistical models involving directed spanning trees, or equivalently non-projective dependency structures. We show how p...
Terry Koo, Amir Globerson, Xavier Carreras, Michae...