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CIA
2006
Springer
15 years 5 months ago
Learning to Negotiate Optimally in Non-stationary Environments
Abstract. We adopt the Markov chain framework to model bilateral negotiations among agents in dynamic environments and use Bayesian learning to enable them to learn an optimal stra...
Vidya Narayanan, Nicholas R. Jennings
BMCBI
2008
117views more  BMCBI 2008»
15 years 2 months ago
Cascaded classifiers for confidence-based chemical named entity recognition
Chemical named entities represent an important facet of biomedical text. We have developed a system to use character-based ngrams, Maximum Entropy Markov Models and rescoring to r...
Peter Corbett, Ann A. Copestake
FUIN
2002
63views more  FUIN 2002»
15 years 1 months ago
Probabilistic Cluster Unfoldings
Abstract. This article introduces probabilistic cluster branching processes, a probabilistic unfolding semantics for untimed Petri nets, with no structural or safety assumptions, g...
Stefan Haar
CP
2010
Springer
15 years 16 days ago
Computing the Density of States of Boolean Formulas
Abstract. In this paper we consider the problem of computing the density of states of a Boolean formula in CNF, a generalization of both MAX-SAT and model counting. Given a Boolean...
Stefano Ermon, Carla P. Gomes, Bart Selman
TOSEM
1998
80views more  TOSEM 1998»
15 years 1 months ago
Discovering Models of Software Processes from Event-Based Data
Many software process methods and tools presuppose the existence of a formal model of a process. Unfortunately, developing a formal model for an on-going, complex process can be d...
Jonathan E. Cook, Alexander L. Wolf