Learning sparse polynomials
Alexandr Andoni, Rina Panigrahy, Gregory Valiant, Li Zhang
SODA | January 2014
Publications
Publications
Publications par année
-
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Nearly optimal minimax estimator for high dimensional sparse linear regression
Li Zhang
Annals of Statistics | January 2013
To appear.
-
Learning functions of halfspaces using prefix covers
Parikshit Gopalan, Adam Klivans, Raghu Meka
COLT'12 | June 2012
Prediction strategies without loss
Michael Kapralov, Rina Panigrahy
January 2012
The minimax risk of truncated series estimators for symmetric convex polytopes
Li Zhang
January 2012
To appear.
-
Differential Privacy and Robust Statistics
Cynthia Dwork
Proceedings of the 41th Annual ACM Symposium on Theory of Computing (STOC) | May 2009
Proceedings of the 41th Annual ACM Symposium on Theory of Computing (STOC)
-
Agnostically Learning Decision Trees
Parikshit Gopalan, Adam Tauman Kalai, Adam R. Klivans
Proceedings of the thirty-ninth annual ACM symposium on Theory of computing (STOC), 2008 | May 2008
ISBN: 978-1-60558-047-0
Filtre par zone de recherche
-
Learning sparse polynomials
Alexandr Andoni, Rina Panigrahy, Gregory Valiant, Li Zhang
SODA | January 2014
Nearly optimal minimax estimator for high dimensional sparse linear regression
Li Zhang
Annals of Statistics | January 2013
To appear.
Learning functions of halfspaces using prefix covers
Parikshit Gopalan, Adam Klivans, Raghu Meka
COLT'12 | June 2012
-
The minimax risk of truncated series estimators for symmetric convex polytopes
Li Zhang
January 2012
To appear.
-
Prediction strategies without loss
Michael Kapralov, Rina Panigrahy
January 2012
Differential Privacy and Robust Statistics
Cynthia Dwork
Proceedings of the 41th Annual ACM Symposium on Theory of Computing (STOC) | May 2009
Proceedings of the 41th Annual ACM Symposium on Theory of Computing (STOC)
-
Differential Privacy and Robust Statistics
Cynthia Dwork
Proceedings of the 41th Annual ACM Symposium on Theory of Computing (STOC) | May 2009
Proceedings of the 41th Annual ACM Symposium on Theory of Computing (STOC)
-
Agnostically Learning Decision Trees
Parikshit Gopalan, Adam Tauman Kalai, Adam R. Klivans
Proceedings of the thirty-ninth annual ACM symposium on Theory of computing (STOC), 2008 | May 2008
ISBN: 978-1-60558-047-0
Publication Type
-
Learning sparse polynomials
Alexandr Andoni, Rina Panigrahy, Gregory Valiant, Li Zhang
SODA | January 2014
Learning functions of halfspaces using prefix covers
Parikshit Gopalan, Adam Klivans, Raghu Meka
COLT'12 | June 2012
Prediction strategies without loss
Michael Kapralov, Rina Panigrahy
January 2012
Differential Privacy and Robust Statistics
Cynthia Dwork
Proceedings of the 41th Annual ACM Symposium on Theory of Computing (STOC) | May 2009
Proceedings of the 41th Annual ACM Symposium on Theory of Computing (STOC)
Agnostically Learning Decision Trees
Parikshit Gopalan, Adam Tauman Kalai, Adam R. Klivans
Proceedings of the thirty-ninth annual ACM symposium on Theory of computing (STOC), 2008 | May 2008
ISBN: 978-1-60558-047-0
-
Nearly optimal minimax estimator for high dimensional sparse linear regression
Li Zhang
Annals of Statistics | January 2013
To appear.
-
The minimax risk of truncated series estimators for symmetric convex polytopes
Li Zhang
January 2012
To appear.