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CVPR
2010
IEEE
14 years 4 months ago
Online-Batch Strongly Convex Multi Kernel Learning
Several object categorization algorithms use kernel methods over multiple cues, as they offer a principled approach to combine multiple cues, and to obtain state-of-theart perform...
Francesco Orabona, Jie Luo, Barbara Caputo
JMLR
2012
11 years 10 months ago
Multi Kernel Learning with Online-Batch Optimization
In recent years there has been a lot of interest in designing principled classification algorithms over multiple cues, based on the intuitive notion that using more features shou...
Francesco Orabona, Jie Luo, Barbara Caputo
APPROX
2007
Springer
137views Algorithms» more  APPROX 2007»
14 years 1 months ago
A Knapsack Secretary Problem with Applications
We consider situations in which a decision-maker with a fixed budget faces a sequence of options, each with a cost and a value, and must select a subset of them online so as to ma...
Moshe Babaioff, Nicole Immorlica, David Kempe, Rob...
COLT
1999
Springer
14 years 17 hour ago
On a Generalized Notion of Mistake Bounds
This paper proposes the use of constructive ordinals as mistake bounds in the on-line learning model. This approach elegantly generalizes the applicability of the on-line mistake ...
Sanjay Jain, Arun Sharma
ICIP
2003
IEEE
14 years 9 months ago
Image compression with on-line and off-line learning
Images typically contain smooth regions, which are easily compressed by linear transforms, and high activity regions (edges, textures), which are harder to compress. To compress t...
Patrice Y. Simard, Christopher J. C. Burges, David...