Abstract. This work presents methods for processing a constraint satisfaction problem (CSP) formulated by an expression-based language, before the CSP is presented to a stochastic ...
Unsupervised learning methods often involve summarizing the data using a small number of parameters. In certain domains, only a small subset of the available data is relevant for ...
We present a logs-based comparison of search patterns across three platforms: computers, iPhones and conventional mobile phones. Our goal is to understand how mobile search users ...
We present GP-HH, a framework for evolving local-search 3-SAT heuristics based on GP. The aim is to obtain “disposable” heuristics which are evolved and used for a specific su...
Background: Recent, rapid growth in the quantity of available genomic data has generated many protein sequences that are not yet biochemically classified. Thus, the prediction of ...