This paper studies the use of discrete-time recurrent neural networks for predicting the next symbol in a sequence. The focus is on online prediction, a task much harder than the c...
This paper investigates the problem of estimating the value of probabilistic parameters needed for decision making in environments in which an agent, operating within a multi-agen...
We present a design of a customized crossbar scheduler for on-chip networks. The proposed scheduler arbitrates on-demand interconnects, where physical topologies are identical to ...
Jae Young Hur, Todor Stefanov, Stephan Wong, Stama...
This paper presents a machine learning approach to the resolution of coreferential relations between nominal constituents in Dutch. It is the first significant automatic approach ...
Enriching speech recognition output with sentence boundaries improves its human readability and enables further processing by downstream language processing modules. We have const...
Yang Liu, Nitesh V. Chawla, Mary P. Harper, Elizab...