A large number of learning algorithms, for example, spectral clustering, kernel Principal Components Analysis and many manifold methods are based on estimating eigenvalues and eig...
In this paper we study the use of experts algorithms in a multiagent setting. In this paper we allow agents to use multiple experts and explore different experts algorithms that a...
This paper describes a method for learning the countability preferences of English nouns from raw text corpora. The method maps the corpus-attested lexico-syntactic properties of ...
Abstract. This paper introduces Deft, a new multitask learning approach for rule learning algorithms. Like other multitask learning systems, the one proposed here is able to improv...
Abstract-- In this paper we investigate the effects of individual learning on an evolving population of situated agents. We work with a novel type of system where agents can decide...