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» GraphLab: A New Framework for Parallel Machine Learning
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ICML
2010
IEEE
13 years 8 months ago
COFFIN: A Computational Framework for Linear SVMs
In a variety of applications, kernel machines such as Support Vector Machines (SVMs) have been used with great success often delivering stateof-the-art results. Using the kernel t...
Sören Sonnenburg, Vojtech Franc
NAACL
2007
13 years 9 months ago
Using "Annotator Rationales" to Improve Machine Learning for Text Categorization
We propose a new framework for supervised machine learning. Our goal is to learn from smaller amounts of supervised training data, by collecting a richer kind of training data: an...
Omar Zaidan, Jason Eisner, Christine D. Piatko
ISPASS
2009
IEEE
14 years 2 months ago
Lonestar: A suite of parallel irregular programs
Until recently, parallel programming has largely focused on the exploitation of data-parallelism in dense matrix programs. However, many important application domains, including m...
Milind Kulkarni, Martin Burtscher, Calin Cascaval,...
COLCOM
2005
IEEE
14 years 1 months ago
Developing a framework for integrating prior problem solving and knowledge sharing histories of a group to predict future group
Using a combination of machine learning probabilistic tools, we have shown that some chemistry students fail to develop productive problem solving strategies through practice alon...
Ron Stevens, Amy Soller, Alessandra Giordani, Luca...
ECTEL
2007
Springer
14 years 1 months ago
Learning Resource Referencing, Search and Aggregation at the eLearning System Level
TELOS is a new eLearning system being built within the Canadian LORNET project. TELOS aims to provide an open operating system in which users can develop and use eLearning and know...
Gilbert Paquette, François Magnan