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KBSE
1997
IEEE
14 years 1 months ago
Genetic Algorithms for Dynamic Test Data Generation
In software testing, it is often desirable to find test inputs that exercise specific program features. To find these inputs by hand is extremely time-consuming, especially whe...
Christoph C. Michael, Gary McGraw, Michael Schatz,...
BMCBI
2011
13 years 3 months ago
Phenotype Recognition with Combined Features and Random Subspace Classifier Ensemble
Background: Automated, image based high-content screening is a fundamental tool for discovery in biological science. Modern robotic fluorescence microscopes are able to capture th...
Bailing Zhang, Tuan D. Pham
CVPR
2009
IEEE
15 years 4 months ago
Efficient Scale Space Auto-Context for Image Segmentation and Labeling
The Conditional Random Fields (CRF) model, using patch-based classification bound with context information, has recently been widely adopted for image segmentation/ labeling. In...
Jiayan Jiang (UCLA), Zhuowen Tu (UCLA)
TCC
2009
Springer
141views Cryptology» more  TCC 2009»
14 years 9 months ago
Weak Verifiable Random Functions
Verifiable random functions (VRFs), introduced by Micali, Rabin and Vadhan, are pseudorandom functions in which the owner of the seed produces a public-key that constitutes a commi...
Zvika Brakerski, Shafi Goldwasser, Guy N. Rothblum...
FOCS
2000
IEEE
14 years 1 months ago
Extracting Randomness via Repeated Condensing
Extractors (defined by Nisan and Zuckerman) are procedures that use a small number of truly random bits (called the seed) to extract many (almost) truly random bits from arbitrar...
Omer Reingold, Ronen Shaltiel, Avi Wigderson