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» On Learning Boolean Functions
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SIGIR
2008
ACM
15 years 6 months ago
Learning to rank with partially-labeled data
Ranking algorithms, whose goal is to appropriately order a set of objects/documents, are an important component of information retrieval systems. Previous work on ranking algorith...
Kevin Duh, Katrin Kirchhoff
KDD
2002
ACM
154views Data Mining» more  KDD 2002»
16 years 7 months ago
Mining Protein Contact Maps
The 3D conformation of a protein may be compactly represented in a symmetrical, square, boolean matrix of pairwise, inter-residue contacts, or "contact map". The contact...
Jingjing Hu, Xiaolan Shen, Yu Shao, Chris Bystroff...
ATS
2009
IEEE
142views Hardware» more  ATS 2009»
16 years 1 months ago
Speeding up SAT-Based ATPG Using Dynamic Clause Activation
Abstract—SAT-based ATPG turned out to be a robust alternative to classical structural ATPG algorithms such as FAN. The number of unclassified faults can be significantly reduce...
Stephan Eggersglüß, Daniel Tille, Rolf ...
DATE
2008
IEEE
122views Hardware» more  DATE 2008»
16 years 1 months ago
Simulation-Directed Invariant Mining for Software Verification
With the advance of SAT solvers, transforming a software program to a propositional formula has generated much interest for bounded model checking of software in recent years. How...
Xueqi Cheng, Michael S. Hsiao
COLT
2005
Springer
16 years 5 days ago
Martingale Boosting
In recent work Long and Servedio [LS05] presented a “martingale boosting” algorithm that works by constructing a branching program over weak classifiers and has a simple anal...
Philip M. Long, Rocco A. Servedio