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ICML
2008
IEEE
16 years 18 days ago
Learning to classify with missing and corrupted features
After a classifier is trained using a machine learning algorithm and put to use in a real world system, it often faces noise which did not appear in the training data. Particularl...
Ofer Dekel, Ohad Shamir
ML
2010
ACM
185views Machine Learning» more  ML 2010»
14 years 6 months ago
Learning to rank on graphs
Graph representations of data are increasingly common. Such representations arise in a variety of applications, including computational biology, social network analysis, web applic...
Shivani Agarwal
CCS
2006
ACM
15 years 3 months ago
Can machine learning be secure?
Machine learning systems offer unparalled flexibility in dealing with evolving input in a variety of applications, such as intrusion detection systems and spam e-mail filtering. H...
Marco Barreno, Blaine Nelson, Russell Sears, Antho...
COLT
2006
Springer
15 years 3 months ago
Online Learning Meets Optimization in the Dual
We describe a novel framework for the design and analysis of online learning algorithms based on the notion of duality in constrained optimization. We cast a sub-family of universa...
Shai Shalev-Shwartz, Yoram Singer
ML
2007
ACM
131views Machine Learning» more  ML 2007»
14 years 11 months ago
A primal-dual perspective of online learning algorithms
We describe a novel framework for the design and analysis of online learning algorithms based on the notion of duality in constrained optimization. We cast a sub-family of universa...
Shai Shalev-Shwartz, Yoram Singer