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DAC
2003
ACM
14 years 10 months ago
A scalable software-based self-test methodology for programmable processors
Software-based self-test (SBST) is an emerging approach to address the challenges of high-quality, at-speed test for complex programmable processors and systems-on chips (SoCs) th...
Li Chen, Srivaths Ravi, Anand Raghunathan, Sujit D...
ECML
2007
Springer
14 years 3 months ago
Statistical Debugging Using Latent Topic Models
Abstract. Statistical debugging uses machine learning to model program failures and help identify root causes of bugs. We approach this task using a novel Delta-Latent-Dirichlet-Al...
David Andrzejewski, Anne Mulhern, Ben Liblit, Xiao...
BMCBI
2006
134views more  BMCBI 2006»
13 years 9 months ago
A statistical score for assessing the quality of multiple sequence alignments
Background: Multiple sequence alignment is the foundation of many important applications in bioinformatics that aim at detecting functionally important regions, predicting protein...
Virpi Ahola, Tero Aittokallio, Mauno Vihinen, Esa ...
JMLR
2012
11 years 11 months ago
A Stick-Breaking Likelihood for Categorical Data Analysis with Latent Gaussian Models
The development of accurate models and efficient algorithms for the analysis of multivariate categorical data are important and longstanding problems in machine learning and compu...
Mohammad Emtiyaz Khan, Shakir Mohamed, Benjamin M....
KSEM
2009
Springer
14 years 3 months ago
A Competitive Learning Approach to Instance Selection for Support Vector Machines
Abstract. Support Vector Machines (SVM) have been applied successfully in a wide variety of fields in the last decade. The SVM problem is formulated as a convex objective function...
Mario Zechner, Michael Granitzer