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» Learning to Solve QBF
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126
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ICDM
2009
IEEE
111views Data Mining» more  ICDM 2009»
15 years 10 months ago
A Game Theoretical Model for Adversarial Learning
Abstract—It is now widely accepted that in many situations where classifiers are deployed, adversaries deliberately manipulate data in order to reduce the classifier’s accura...
Wei Liu, Sanjay Chawla
106
Voted
SOUPS
2009
ACM
15 years 10 months ago
Machine learning attacks against the Asirra CAPTCHA
The ASIRRA CAPTCHA [6], recently proposed at ACM CCS 2007, relies on the problem of distinguishing images of cats and dogs (a task that humans are very good at). The security of AS...
Philippe Golle
126
Voted
AI
2007
Springer
15 years 10 months ago
Learning the Semantic Meaning of a Concept from the Web
Many researchers have used text classification method in solving the ontology mapping problem. Their mapping results heavily depend on the availability of quality exemplars used as...
Yang Yu, Yun Peng
118
Voted
GECCO
2007
Springer
137views Optimization» more  GECCO 2007»
15 years 10 months ago
Learning and anticipation in online dynamic optimization with evolutionary algorithms: the stochastic case
The focus of this paper is on how to design evolutionary algorithms (EAs) for solving stochastic dynamic optimization problems online, i.e. as time goes by. For a proper design, t...
Peter A. N. Bosman, Han La Poutré
117
Voted
CIBCB
2006
IEEE
15 years 9 months ago
Machine Learning in Basecalling Decoding Trace Peak Behaviour
— DNA sequence basecalling is commonly regarded as a solved problem, despite significant error rates being reflected in inaccuracies in databases and genome annotations. These er...
David Thornley, Stavros Petridis