Hsu et al. (2009) recently proposed an efficient, accurate spectral learning algorithm for Hidden Markov Models (HMMs). In this paper we relax their assumptions and prove a tighte...
Human-nameable visual “attributes” can benefit various recognition tasks. However, existing techniques restrict these properties to categorical labels (for example, a person ...
Abstract. We present a survey of recent results concerning the theoretical and empirical performance of algorithms for learning regularized least-squares classifiers. The behavior ...
In this work, we study the problem of within-network relational learning and inference, where models are learned on a partially labeled relational dataset and then are applied to ...
Words are the essence of communication: they are the building blocks of any language. Learning the meaning of words is thus one of the most important aspects of language acquisiti...