Finite-domain constraint programming has been used with great success to tackle a wide variety of combinatorial problems in industry and academia. To apply finite-domain constrain...
Alan M. Frisch, Brahim Hnich, Zeynep Kiziltan, Ian...
In this paper we present a variational Bayes (VB) framework for learning continuous hidden Markov models (CHMMs), and we examine the VB framework within active learning. Unlike a ...
The study of networked systems is an emerging field, impacting almost every area of engineering and science, including the important domains of communication systems, biology, soc...
Pseudo-relevance feedback (PRF) improves search quality by expanding the query using terms from high-ranking documents from an initial retrieval. Although PRF can often result in ...
Marc-Allen Cartright, James Allan, Victor Lavrenko...
Abstract. This paper introduces the notion of finite precision timed automata (FPTAs) and proposes a data structure to represent its symbolic states. To reduce the state space, FP...