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» GraphLab: A New Framework for Parallel Machine Learning
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ICML
2010
IEEE
13 years 8 months ago
On learning with kernels for unordered pairs
We propose and analyze two strategies to learn over unordered pairs with kernels, and provide a common theoretical framework to compare them. The strategies are related to methods...
Martial Hue, Jean-Philippe Vert
CGO
2010
IEEE
14 years 2 months ago
Decoupled software pipelining creates parallelization opportunities
Decoupled Software Pipelining (DSWP) is one approach to automatically extract threads from loops. It partitions loops into long-running threads that communicate in a pipelined man...
Jialu Huang, Arun Raman, Thomas B. Jablin, Yun Zha...
ICPP
2009
IEEE
14 years 2 months ago
Exploiting Simulation Slack to Improve Parallel Simulation Speed
Parallel simulation is a technique to accelerate microarchitecture simulation of CMPs by exploiting the inherent parallelism of CMPs. In this paper, we explore the simulation para...
Jianwei Chen, Murali Annavaram, Michel Dubois
NAACL
2007
13 years 9 months ago
Source-Language Features and Maximum Correlation Training for Machine Translation Evaluation
We propose three new features for MT evaluation: source-sentence constrained n-gram precision, source-sentence reordering metrics, and discriminative unigram precision, as well as...
Ding Liu, Daniel Gildea
IPPS
2009
IEEE
14 years 2 months ago
Building a parallel pipelined external memory algorithm library
Large and fast hard disks for little money have enabled the processing of huge amounts of data on a single machine. For this purpose, the well-established STXXL library provides a...
Andreas Beckmann, Roman Dementiev, Johannes Single...