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CORR
2011
Springer
199views Education» more  CORR 2011»
13 years 4 months ago
Fast Sparse Matrix-Vector Multiplication on GPUs: Implications for Graph Mining
Scaling up the sparse matrix-vector multiplication kernel on modern Graphics Processing Units (GPU) has been at the heart of numerous studies in both academia and industry. In thi...
Xintian Yang, Srinivasan Parthasarathy, Ponnuswamy...
NIPS
2008
13 years 10 months ago
Supervised Dictionary Learning
It is now well established that sparse signal models are well suited for restoration tasks and can be effectively learned from audio, image, and video data. Recent research has be...
Julien Mairal, Francis Bach, Jean Ponce, Guillermo...
ICML
2005
IEEE
14 years 9 months ago
Building Sparse Large Margin Classifiers
This paper presents an approach to build Sparse Large Margin Classifiers (SLMC) by adding one more constraint to the standard Support Vector Machine (SVM) training problem. The ad...
Bernhard Schölkopf, Gökhan H. Bakir, Min...
PAKDD
2004
ACM
127views Data Mining» more  PAKDD 2004»
14 years 2 months ago
Separating Structure from Interestingness
Condensed representations of pattern collections have been recognized to be important building blocks of inductive databases, a promising theoretical framework for data mining, and...
Taneli Mielikäinen
CIMAGING
2010
195views Hardware» more  CIMAGING 2010»
13 years 10 months ago
SPIRAL out of convexity: sparsity-regularized algorithms for photon-limited imaging
The observations in many applications consist of counts of discrete events, such as photons hitting a detector, which cannot be effectively modeled using an additive bounded or Ga...
Zachary T. Harmany, Roummel F. Marcia, Rebecca Wil...