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ISMB
1993
15 years 8 months ago
Protein Structure Prediction: Selecting Salient Features from Large Candidate Pools
Weintroduce a parallel approach, "DT-SELECT," for selecting features used by inductive learning algorithms to predict protein secondary structure. DT-SELECTis able to ra...
Kevin J. Cherkauer, Jude W. Shavlik
CVPR
2009
IEEE
1390views Computer Vision» more  CVPR 2009»
17 years 2 months ago
Stacks of Convolutional Restricted Boltzmann Machines for Shift-Invariant Feature Learning
In this paper we present a method for learning classspecific features for recognition. Recently a greedy layerwise procedure was proposed to initialize weights of deep belief ne...
Mohammad Norouzi (Simon Fraser University), Mani R...
ICDAR
2007
IEEE
16 years 1 months ago
A Sparse and Locally Shift Invariant Feature Extractor Applied to Document Images
We describe an unsupervised learning algorithm for extracting sparse and locally shift-invariant features. We also devise a principled procedure for learning hierarchies of invari...
Marc'Aurelio Ranzato, Yann LeCun
ECAI
2010
Springer
15 years 4 months ago
Feature Selection by Approximating the Markov Blanket in a Kernel-Induced Space
The proposed feature selection method aims to find a minimum subset of the most informative variables for classification/regression by efficiently approximating the Markov Blanket ...
Qiang Lou, Zoran Obradovic
BROADNETS
2007
IEEE
16 years 1 months ago
Modeling and analysis of worm interactions (war of the worms)
—“War of the worms” is a war between opposing computer worms, creating complex worm interactions as well as detrimental impact on infrastructure. For example, in September 20...
Sapon Tanachaiwiwat, Ahmed Helmy