Ontologies are an increasingly important tool in knowledge representation, as they allow large amounts of data to be related in a logical fashion. Current research is concentrated...
Matthew E. Taylor, Cynthia Matuszek, Bryan Klimt, ...
Rule extraction is a technique aimed at transforming highly accurate opaque models like neural networks into comprehensible models without losing accuracy. G-REX is a rule extract...
Current studies have demonstrated that the representational power of predictive state representations (PSRs) is at least equal to the one of partially observable Markov decision p...
Abdeslam Boularias, Masoumeh T. Izadi, Brahim Chai...
Importance Sampling is a potentially powerful variance reduction technique to speed up simulations where the objective depends on the occurrence of rare events. However, it is cru...
Clustering is a common problem in the analysis of large data sets. Streaming algorithms, which make a single pass over the data set using small working memory and produce a cluster...