In earlier work we have introduced and explored a variety of different probabilistic models for the problem of answering selectivity queries posed to large sparse binary data set...
A central problem in learning in complex environmentsis balancing exploration of untested actions against exploitation of actions that are known to be good. The benefit of explora...
A critical path in the development of natural language understanding NLU modules lies in the di culty of de ning a mapping from words to semantics: Usually it takes in the order o...
We formulate a principle for classification with the knowledge of the marginal distribution over the data points (unlabeled data). The principle is cast in terms of Tikhonov styl...
Corpus-based methods for natural language processing often use supervised training, requiring expensive manual annotation of training corpora. This paper investigates methods for ...