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ICCV
2011
IEEE
12 years 7 months ago
Perturb-and-MAP Random Fields: Using Discrete Optimization\\to Learn and Sample from Energy Models
We propose a novel way to induce a random field from an energy function on discrete labels. It amounts to locally injecting noise to the energy potentials, followed by finding t...
George Papandreou, Alan L. Yuille
CONCUR
2005
Springer
14 years 1 months ago
A Theory of System Behaviour in the Presence of Node and Link Failures
d Abstract) Adrian Francalanza and Matthew Hennessy University of Sussex, Falmer Brighton BN1 9RH, England Abstract. We develop a behavioural theory of distributed programs in the ...
Adrian Francalanza, Matthew Hennessy
FORTE
2004
13 years 9 months ago
Symbolic Performance and Dependability Evaluation with the Tool CASPA
This paper describes the tool CASPA, a new performance evaluation tool which is based on a Markovian stochastic process algebra. CASPA uses multi-terminal binary decision diagrams ...
Matthias Kuntz, Markus Siegle, Edith Werner
EMNLP
2007
13 years 9 months ago
Bootstrapping Information Extraction from Field Books
We present two machine learning approaches to information extraction from semi-structured documents that can be used if no annotated training data are available, but there does ex...
Sander Canisius, Caroline Sporleder
BMCBI
2005
114views more  BMCBI 2005»
13 years 7 months ago
A new decoding algorithm for hidden Markov models improves the prediction of the topology of all-beta membrane proteins
Background: Structure prediction of membrane proteins is still a challenging computational problem. Hidden Markov models (HMM) have been successfully applied to the problem of pre...
Piero Fariselli, Pier Luigi Martelli, Rita Casadio