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85
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COLT
2008
Springer
15 years 2 months ago
High-Probability Regret Bounds for Bandit Online Linear Optimization
We present a modification of the algorithm of Dani et al. [8] for the online linear optimization problem in the bandit setting, which with high probability has regret at most O ( ...
Peter L. Bartlett, Varsha Dani, Thomas P. Hayes, S...
98
Voted
NIPS
2003
15 years 2 months ago
Online Passive-Aggressive Algorithms
We present a family of margin based online learning algorithms for various prediction tasks. In particular we derive and analyze algorithms for binary and multiclass categorizatio...
Shai Shalev-Shwartz, Koby Crammer, Ofer Dekel, Yor...
CORR
2010
Springer
165views Education» more  CORR 2010»
15 years 26 days ago
Online Learning: Beyond Regret
We study online learnability of a wide class of problems, extending the results of [26] to general notions of performance measure well beyond external regret. Our framework simult...
Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari
IJET
2006
40views more  IJET 2006»
15 years 23 days ago
An open source information system for online counseling for a Mexican university
One of the primary goals of undergraduate studies programs is to promote the professional and personal growth and success of their students. First year students, however, often suf...
Arthur Walter Edwards
112
Voted
CVPR
2012
IEEE
13 years 3 months ago
Incremental gradient on the Grassmannian for online foreground and background separation in subsampled video
It has recently been shown that only a small number of samples from a low-rank matrix are necessary to reconstruct the entire matrix. We bring this to bear on computer vision prob...
Jun He, Laura Balzano, Arthur Szlam