In this paper we propose a data intensive approach for inferring sentence-internal temporal relations. Temporal inference is relevant for practical NLP applications which either e...
We present a vision-based method that assists human
navigation within unfamiliar environments. Our main contribution
is a novel algorithm that learns the correlation between
use...
We discuss an important property called the asymptotic equipartition property on empirical sequences in reinforcement learning. This states that the typical set of empirical seque...
We present a novel system that helps nonexperts find sets of similar words. The user begins by specifying one or more seed words. The system then iteratively suggests a series of ...
We address the learning of trust based on past observations and context information. We argue that from the truster's point of view trust is best expressed as one of several ...