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» GraphLab: A New Framework for Parallel Machine Learning
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ML
2008
ACM
135views Machine Learning» more  ML 2008»
15 years 2 months ago
Compiling pattern matching to good decision trees
We address the issue of compiling ML pattern matching to compact and efficient decisions trees. Traditionally, compilation to decision trees is optimized by (1) implementing decis...
Luc Maranget
122
Voted
HT
2005
ACM
15 years 8 months ago
As we may perceive: inferring logical documents from hypertext
In recent years, many algorithms for the Web have been developed that work with information units distinct from individual web pages. These include segments of web pages or aggreg...
Pavel Dmitriev, Carl Lagoze, Boris Suchkov
118
Voted
IPPS
2010
IEEE
15 years 14 days ago
On the parallelisation of MCMC by speculative chain execution
Abstract--The increasing availability of multi-core and multiprocessor architectures provides new opportunities for improving the performance of many computer simulations. Markov C...
Jonathan M. R. Byrd, Stephen A. Jarvis, Abhir H. B...
USS
2010
15 years 12 days ago
P4P: Practical Large-Scale Privacy-Preserving Distributed Computation Robust against Malicious Users
In this paper we introduce a framework for privacypreserving distributed computation that is practical for many real-world applications. The framework is called Peers for Privacy ...
Yitao Duan, NetEase Youdao, John Canny, Justin Z. ...
134
Voted
ESANN
2004
15 years 4 months ago
Sparse LS-SVMs using additive regularization with a penalized validation criterion
This paper is based on a new way for determining the regularization trade-off in least squares support vector machines (LS-SVMs) via a mechanism of additive regularization which ha...
Kristiaan Pelckmans, Johan A. K. Suykens, Bart De ...