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» GraphLab: A New Framework for Parallel Machine Learning
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ICML
2005
IEEE
14 years 8 months ago
New approaches to support vector ordinal regression
In this paper, we propose two new support vector approaches for ordinal regression, which optimize multiple thresholds to define parallel discriminant hyperplanes for the ordinal ...
Wei Chu, S. Sathiya Keerthi
PLDI
1996
ACM
13 years 11 months ago
Commutativity Analysis: A New Analysis Framework for Parallelizing Compilers
This paper presents a new analysis technique, commutativity analysis, for automatically parallelizing computations that manipulate dynamic, pointer-based data structures. Commutat...
Martin C. Rinard, Pedro C. Diniz
ICMLA
2009
13 years 5 months ago
Ranking Electrical Feeders of the New York Power Grid
components of a system by susceptibility to failure. In this extended abstract, we present an ongoing project to rank the underground primary feeders of Consolidated Edison Company...
Philip Gross, Ansaf Salleb-Aouissi, Haimonti Dutta...
ICCV
2007
IEEE
14 years 1 months ago
Co-Tracking Using Semi-Supervised Support Vector Machines
This paper treats tracking as a foreground/background classification problem and proposes an online semisupervised learning framework. Initialized with a small number of labeled ...
Feng Tang, Shane Brennan, Qi Zhao, Hai Tao
ICML
2000
IEEE
13 years 12 months ago
A Bayesian Framework for Reinforcement Learning
The reinforcement learning problem can be decomposed into two parallel types of inference: (i) estimating the parameters of a model for the underlying process; (ii) determining be...
Malcolm J. A. Strens