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» Bounds for Linear Multi-Task Learning
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COLT
2001
Springer
14 years 1 days ago
Ultraconservative Online Algorithms for Multiclass Problems
In this paper we study a paradigm to generalize online classification algorithms for binary classification problems to multiclass problems. The particular hypotheses we investig...
Koby Crammer, Yoram Singer
JMLR
2011
148views more  JMLR 2011»
13 years 2 months ago
Multitask Sparsity via Maximum Entropy Discrimination
A multitask learning framework is developed for discriminative classification and regression where multiple large-margin linear classifiers are estimated for different predictio...
Tony Jebara
ICML
2007
IEEE
14 years 8 months ago
Pegasos: Primal Estimated sub-GrAdient SOlver for SVM
We describe and analyze a simple and effective iterative algorithm for solving the optimization problem cast by Support Vector Machines (SVM). Our method alternates between stocha...
Shai Shalev-Shwartz, Yoram Singer, Nathan Srebro
STOC
2001
ACM
104views Algorithms» more  STOC 2001»
14 years 7 months ago
Spatial gossip and resource location protocols
The dynamic behavior of a network in which information is changing continuously over time requires robust and efficient mechanisms for keeping nodes updated about new information. ...
David Kempe, Jon M. Kleinberg, Alan J. Demers
ICML
2006
IEEE
14 years 8 months ago
Totally corrective boosting algorithms that maximize the margin
We consider boosting algorithms that maintain a distribution over a set of examples. At each iteration a weak hypothesis is received and the distribution is updated. We motivate t...
Gunnar Rätsch, Jun Liao, Manfred K. Warmuth