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...
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...
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 ...
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....
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...