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112
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CVPR
2008
IEEE
16 years 3 months ago
Dimensionality reduction using covariance operator inverse regression
We consider the task of dimensionality reduction for regression (DRR) whose goal is to find a low dimensional representation of input covariates, while preserving the statistical ...
Minyoung Kim, Vladimir Pavlovic
ARITH
2005
IEEE
15 years 7 months ago
Fast Modular Reduction for Large Wordlengths via One Linear and One Cyclic Convolution
Abstract— Modular reduction is a fundamental operation in cryptographic systems. Most well known modular reduction methods including Barrett’s and Montgomery’s algorithms lev...
Dhananjay S. Phatak, Tom Goff
114
Voted
AAI
2010
94views more  AAI 2010»
14 years 9 months ago
Sequence-Indexed Linear-Time Temporal Logic: Proof System and Application
In this paper, we propose a proof system for reasoning on certain specifications of secure authentication systems. For this purpose, a new logic, sequence-indexed linear-time temp...
Ken Kaneiwa, Norihiro Kamide
ENTCS
2010
127views more  ENTCS 2010»
15 years 1 months ago
Combining Model Reductions
Molecular biological models usually suffer from a large combinatorial explosion. Indeed, proteins form complexes and modify each others, which leads to the formation of a huge num...
Ferdinanda Camporesi, Jérôme Feret, H...
110
Voted
JMLR
2006
143views more  JMLR 2006»
15 years 1 months ago
Geometric Variance Reduction in Markov Chains: Application to Value Function and Gradient Estimation
We study a sequential variance reduction technique for Monte Carlo estimation of functionals in Markov Chains. The method is based on designing sequential control variates using s...
Rémi Munos