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» Learning and using relational theories
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ICML
2004
IEEE
14 years 10 months ago
Margin based feature selection - theory and algorithms
Feature selection is the task of choosing a small set out of a given set of features that capture the relevant properties of the data. In the context of supervised classification ...
Ran Gilad-Bachrach, Amir Navot, Naftali Tishby
WWW
2009
ACM
14 years 10 months ago
Learning to recognize reliable users and content in social media with coupled mutual reinforcement
Community Question Answering (CQA) has emerged as a popular forum for users to pose questions for other users to answer. Over the last few years, CQA portals such as Naver and Yah...
Jiang Bian, Yandong Liu, Ding Zhou, Eugene Agichte...
ICML
2003
IEEE
14 years 10 months ago
Using Linear-threshold Algorithms to Combine Multi-class Sub-experts
We present a new type of multi-class learning algorithm called a linear-max algorithm. Linearmax algorithms learn with a special type of attribute called a sub-expert. A sub-exper...
Chris Mesterharm
POPL
2012
ACM
12 years 5 months ago
Probabilistic relational reasoning for differential privacy
Differential privacy is a notion of confidentiality that protects the privacy of individuals while allowing useful computations on their private data. Deriving differential priva...
Gilles Barthe, Boris Köpf, Federico Olmedo, S...
ALT
2008
Springer
14 years 7 months ago
Prequential Randomness
This paper studies Dawid’s prequential framework from the point of view of the algorithmic theory of randomness. The main result is that two natural notions of randomness coincid...
Vladimir Vovk, Alexander Shen