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FOCS
2010
IEEE
14 years 10 months ago
Boosting and Differential Privacy
Boosting is a general method for improving the accuracy of learning algorithms. We use boosting to construct improved privacy-preserving synopses of an input database. These are da...
Cynthia Dwork, Guy N. Rothblum, Salil P. Vadhan
EUROGP
2010
Springer
166views Optimization» more  EUROGP 2010»
15 years 5 months ago
Learning a Lot from Only a Little: Genetic Programming for Panel Segmentation on Sparse Sensory Evaluation Data
We describe a data mining framework that derives panelist information from sparse flavour survey data. One component of the framework executes genetic programming ensemble based s...
Katya Vladislavleva, Kalyan Veeramachaneni, Una-Ma...
105
Voted
KBSE
2009
IEEE
15 years 7 months ago
Reggae: Automated Test Generation for Programs Using Complex Regular Expressions
Abstract—Test coverage such as branch coverage is commonly measured to assess the sufficiency of test inputs. To reduce tedious manual efforts in generating high-covering test i...
Nuo Li, Tao Xie, Nikolai Tillmann, Jonathan de Hal...
113
Voted
CCS
2010
ACM
15 years 23 days ago
Input generation via decomposition and re-stitching: finding bugs in Malware
Attackers often take advantage of vulnerabilities in benign software, and the authors of benign software must search their code for bugs in hopes of finding vulnerabilities before...
Juan Caballero, Pongsin Poosankam, Stephen McCaman...
113
Voted
ASPLOS
2012
ACM
13 years 8 months ago
Path-exploration lifting: hi-fi tests for lo-fi emulators
Processor emulators are widely used to provide isolation and instrumentation of binary software. However they have proved difficult to implement correctly: processor specificati...
Lorenzo Martignoni, Stephen McCamant, Pongsin Poos...