We explore an algorithm for training SVMs with Kernels that can represent the learned rule using arbitrary basis vectors, not just the support vectors (SVs) from the training set. ...
The performance of supervised learners depends on the presence of a relatively large labeled sample. This paper proposes an automatic ongoing learning system, which is able to inco...
Decision trees are among the most effective and interpretable classification algorithms while ensembles techniques have been proven to alleviate problems regarding over-fitting and...
We present a novel system for automatically marking up text documents into XML and discuss the benefits of XML markup for intelligent information retrieval. The system uses the Se...
Abstract. We address the issue of efficiently automating assume-guarantee reasoning for simulation conformance between finite state systems and specifications. We focus on a non...
Sagar Chaki, Edmund M. Clarke, Nishant Sinha, Pras...