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PPOPP
2011
ACM
14 years 16 days ago
Programming the memory hierarchy revisited: supporting irregular parallelism in sequoia
We describe two novel constructs for programming parallel machines with multi-level memory hierarchies: call-up, which allows a child task to invoke computation on its parent, and...
Michael Bauer, John Clark, Eric Schkufza, Alex Aik...
ECAI
2004
Springer
15 years 3 months ago
A Generalized Quadratic Loss for Support Vector Machines
The standard SVM formulation for binary classification is based on the Hinge loss function, where errors are considered not correlated. Due to this, local information in the featu...
Filippo Portera, Alessandro Sperduti
CIBCB
2006
IEEE
15 years 3 months ago
Visualization of Support Vector Machines with Unsupervised Learning
– The visualization of support vector machines in realistic settings is a difficult problem due to the high dimensionality of the typical datasets involved. However, such visuali...
Lutz Hamel
AAAI
2006
14 years 11 months ago
Multiclass Support Vector Machines for Articulatory Feature Classification
of somewhat abstracting away from the literal physiological measurements of articulation that are so closely tied to the acoustic signal, and with some additional computational bur...
Brian Hutchinson, Jianna Zhang
CVPR
2005
IEEE
15 years 11 months ago
A Sparse Support Vector Machine Approach to Region-Based Image Categorization
Automatic image categorization using low-level features is a challenging research topic in computer vision. In this paper, we formulate the image categorization problem as a multi...
Jinbo Bi, Yixin Chen, James Ze Wang