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NIPS
2001
13 years 7 months ago
Efficiency versus Convergence of Boolean Kernels for On-Line Learning Algorithms
The paper studies machine learning problems where each example is described using a set of Boolean features and where hypotheses are represented by linear threshold elements. One ...
Roni Khardon, Dan Roth, Rocco A. Servedio
ALT
2007
Springer
13 years 12 months ago
Online Regression Competitive with Changing Predictors
This paper deals with the problem of making predictions in the online mode of learning where the dependence of the outcome yt on the signal xt can change with time. The Aggregating...
Steven Busuttil, Yuri Kalnishkan
ICDM
2006
IEEE
119views Data Mining» more  ICDM 2006»
13 years 11 months ago
Fast On-line Kernel Learning for Trees
Kernel methods have been shown to be very effective for applications requiring the modeling of structured objects. However kernels for structures usually are too computational dem...
Fabio Aiolli, Giovanni Da San Martino, Alessandro ...
JMLR
2012
11 years 8 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
CVPR
2010
IEEE
14 years 2 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