In this work, we discuss practical methods for the assessment, comparison, and selection of complex hierarchical Bayesian models. A natural way to assess the goodness of the model...
Abstract. Bayesian reinforcement learning (RL) is aimed at making more efficient use of data samples, but typically uses significantly more computation. For discrete Markov Decis...
Models of language learning play a central role in a wide range of applications: from psycholinguistic theories of how people acquire new word knowledge, to information systems th...
The Syntactic Concept Lattice is a residuated lattice based on the distributional structure of a language; the natural representation based on this is a context sensitive formalism...
We present a novel framework to estimate protein-protein (PPI) and domain-domain (DDI) interactions based on a belief propagation estimation method that efficiently computes inter...
Faruck Morcos, Marcin Sikora, Mark S. Alber, Dale ...