Large margin learning of Continuous Density HMMs with a partially labeled dataset has been extensively studied in the speech and handwriting recognition fields. Yet due to the non...
Many factorization models like matrix or tensor factorization have been proposed for the important application of recommender systems. The success of such factorization models dep...
This paper develops Probabilistic Hybrid Action Models (PHAMs), a realistic causal model for predicting the behavior generated by modern concurrent percept-driven robot plans. PHA...
—Robust and flexible speech codecs are required more and more by speech communication over unreliable and heterogeneous channels such as the internet. In this paper, a novel mult...
In this paper, we develop a queuing theory based analytical model to evaluate the performance of transactional memory. Based on the statistical characteristics observed on actual e...