Semi-supervised learning has emerged as a popular framework for improving modeling accuracy while controlling labeling cost. Based on an extension of stochastic composite likeliho...
Joshua Dillon, Krishnakumar Balasubramanian, Guy L...
We describe a framework for inducing probabilistic grammars from corpora of positive samples. First, samples are incorporated by adding ad-hoc rules to a working grammar; subseque...
We present a conceptual framework for validating reusable behavioral models. The setting for this work is a modern product development environment in which design is performed by ...
The development of a discrete-event simulation tool, called GMSim, based on the generalized semi-Markov process (GSMP) formalism is described. The GSMP representation comprises bo...
Interaction with the environment is a key factor affecting the development of plants and plant ecosystems. In this paper we introduce a modeling framework that makes it possible t...