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» Parallel matrix algorithms and applications
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144
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KDD
2012
ACM
207views Data Mining» more  KDD 2012»
13 years 3 months ago
Robust multi-task feature learning
Multi-task learning (MTL) aims to improve the performance of multiple related tasks by exploiting the intrinsic relationships among them. Recently, multi-task feature learning alg...
Pinghua Gong, Jieping Ye, Changshui Zhang
102
Voted
ICML
2009
IEEE
16 years 1 months ago
Large-scale deep unsupervised learning using graphics processors
The promise of unsupervised learning methods lies in their potential to use vast amounts of unlabeled data to learn complex, highly nonlinear models with millions of free paramete...
Rajat Raina, Anand Madhavan, Andrew Y. Ng
114
Voted
PPOPP
2010
ACM
15 years 10 months ago
Lazy binary-splitting: a run-time adaptive work-stealing scheduler
We present Lazy Binary Splitting (LBS), a user-level scheduler of nested parallelism for shared-memory multiprocessors that builds on existing Eager Binary Splitting work-stealing...
Alexandros Tzannes, George C. Caragea, Rajeev Baru...
SAC
2009
ACM
15 years 7 months ago
GTfold: a scalable multicore code for RNA secondary structure prediction
The prediction of the correct secondary structures of large RNAs is one of the unsolved challenges of computational molecular biology. Among the major obstacles is the fact that a...
Amrita Mathuriya, David A. Bader, Christine E. Hei...
120
Voted
HPDC
2009
IEEE
15 years 7 months ago
TakTuk, adaptive deployment of remote executions
This article deals with TakTuk, a middleware that deploys efficiently parallel remote executions on large scale grids (thousands of nodes). This tool is mostly intended for intera...
Benoit Claudel, Guillaume Huard, Olivier Richard