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» Quantified Conditionals and Compositionality
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ICWS
2009
IEEE
13 years 5 months ago
A MapReduce-Enabled Scientific Workflow Composition Framework
MapReduce has recently gained a lot of attention as a parallel programming model for scalable data-intensive business and scientific analysis. In order to benefit from this powerf...
Xubo Fei, Shiyong Lu, Cui Lin
JMLR
2010
165views more  JMLR 2010»
13 years 2 months ago
Learning with Blocks: Composite Likelihood and Contrastive Divergence
Composite likelihood methods provide a wide spectrum of computationally efficient techniques for statistical tasks such as parameter estimation and model selection. In this paper,...
Arthur Asuncion, Qiang Liu, Alexander T. Ihler, Pa...
IOR
2011
152views more  IOR 2011»
13 years 2 months ago
Risk-Averse Two-Stage Stochastic Linear Programming: Modeling and Decomposition
We formulate a risk-averse two-stage stochastic linear programming problem in which unresolved uncertainty remains after the second stage. The objective function is formulated as ...
Naomi Miller, Andrzej Ruszczynski
IEEEPACT
2007
IEEE
14 years 1 months ago
Verification-Aware Microprocessor Design
The process of verifying a new microprocessor is a major problem for the computer industry. Currently, architects design processors to be fast, power-efficient, and reliable. Howe...
Anita Lungu, Daniel J. Sorin
ICML
2010
IEEE
13 years 8 months ago
Asymptotic Analysis of Generative Semi-Supervised Learning
Semi-supervised learning has emerged as a popular framework for improving modeling accuracy while controlling labeling cost. Based on an extension of stochastic composite likeliho...
Joshua Dillon, Krishnakumar Balasubramanian, Guy L...