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CVPR
2007
IEEE
16 years 8 months ago
Eigenboosting: Combining Discriminative and Generative Information
A major shortcoming of discriminative recognition and detection methods is their noise sensitivity, both during training and recognition. This may lead to very sensitive and britt...
Helmut Grabner, Peter M. Roth, Horst Bischof
DAC
2003
ACM
16 years 7 months ago
Coverage directed test generation for functional verification using bayesian networks
Functional verification is widely acknowledged as the bottleneck in the hardware design cycle. This paper addresses one of the main challenges of simulation based verification (or...
Shai Fine, Avi Ziv
ICML
2005
IEEE
16 years 7 months ago
Discriminative versus generative parameter and structure learning of Bayesian network classifiers
In this paper, we compare both discriminative and generative parameter learning on both discriminatively and generatively structured Bayesian network classifiers. We use either ma...
Franz Pernkopf, Jeff A. Bilmes
SIGSOFT
2008
ACM
16 years 7 months ago
Experience in using a process language to define scientific workflow and generate dataset provenance
This paper describes our experiences in exploring the applicability of software engineering approaches to scientific data management problems. Specifically, this paper describes h...
Leon J. Osterweil, Lori A. Clarke, Aaron M. Elliso...
CADE
2004
Springer
16 years 7 months ago
Automatic Generation of Classification Theorems for Finite Algebras
Abstract. Classifying finite algebraic structures has been a major motivation behind much research in pure mathematics. Automated techniques have aided in this process, but this ha...
Simon Colton, Andreas Meier, Volker Sorge, Roy L. ...