This paper addresses feature selection techniques for classification of high dimensional data, such as those produced by microarray experiments. Some prior knowledge may be availa...
We propose a new statistical approach to extracting personal names from a corpus. One of the key points of our approach is that it can both automatically learn the characteristics...
We consider the problem of PAC-learning distributions over strings, represented by probabilistic deterministic finite automata (PDFAs). PDFAs are a probabilistic model for the gen...
Dynamic protocol recovery tries to recover a component’s sequencing constraints by means of dynamic analysis. This problem has been tackled by several automaton learning approac...
In this paper, we explore the differences between the Adaptive Hypermedia and IMS Simple Sequencing approaches. Both approaches provide learning material tailored for the learner...