Abstract. We present a survey of recent results concerning the theoretical and empirical performance of algorithms for learning regularized least-squares classifiers. The behavior ...
Stochastic context-free grammars (SCFGs) have long been recognized as useful for a large variety of tasks including natural language processing, morphological parsing, speech reco...
Natural languages are easy to learn by infants, they can express any thought that any adult might ever conceive, and they accommodate the limitations of human breathing rates and s...
Dynamic Bayesian networks (DBNs) offer an elegant way to integrate various aspects of language in one model. Many existing algorithms developed for learning and inference in DBNs ...
Knowledge processing is very demanding on computer architectures. Knowledge processing generates subcomputation paths at an exponential rate. It is memory intensive and has high c...