Many language implementations, particularly for high-level and scripting languages, are based on carefully honed runtime systems that have an internally sequential execution model...
James Swaine, Kevin Tew, Peter A. Dinda, Robert Br...
We present an application of the analytical inductive programming system Igor to learning sets of recursive rules from positive experience. We propose that this approach can be us...
In this paper we propose a genetic programming approach to learning stochastic models with unsymmetrical noise distributions. Most learning algorithms try to learn from noisy data...
The paper describes a lexicon driven approach for word recognition on handwritten documents using Conditional Random Fields(CRFs). CRFs are discriminative models and do not make a...
Shravya Shetty, Harish Srinivasan, Sargur N. Sriha...
This paper describes SKIMA, a mediation system that gives transparent access to heterogeneous and distributed sources considering their semantics and the semantics of application ...