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» Extracting Randomness Using Few Independent Sources
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NIPS
2004
13 years 8 months ago
Nonlinear Blind Source Separation by Integrating Independent Component Analysis and Slow Feature Analysis
In contrast to the equivalence of linear blind source separation and linear independent component analysis it is not possible to recover the original source signal from some unkno...
Tobias Blaschke, Laurenz Wiskott
ICASSP
2009
IEEE
14 years 2 months ago
Combining independent component analysis with geometric information and its application to speech processing
In this paper, we propose two approaches for combining geometric information with ICA algorithm to solve permutation problem under the scenario where a rough information about the...
Wenyi Zhang, Bhaskar D. Rao
FOCS
2009
IEEE
14 years 2 months ago
2-Source Extractors under Computational Assumptions and Cryptography with Defective Randomness
Abstract— We show how to efficiently extract truly random bits from two independent sources of linear min-entropy, under a computational assumption. The assumption we rely on is...
Yael Tauman Kalai, Xin Li, Anup Rao
KES
2010
Springer
13 years 5 months ago
Extracting Principal Components from Pseudo-random Data by Using Random Matrix Theory
We develop a methodology to grasp temporal trend in a stock market that changes year to year, or sometimes within a year depending on numerous factors. For this purpose, we employ ...
Mieko Tanaka-Yamawaki
AAAI
2007
13 years 9 months ago
Template-Independent News Extraction Based on Visual Consistency
Wrapper is a traditional method to extract useful information from Web pages. Most previous works rely on the similarity between HTML tag trees and induced template-dependent wrap...
Shuyi Zheng, Ruihua Song, Ji-Rong Wen