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TIT
2008
76views more  TIT 2008»
13 years 7 months ago
Improved Risk Tail Bounds for On-Line Algorithms
We prove the strongest known bound for the risk of hypotheses selected from the ensemble generated by running a learning algorithm incrementally on the training data. Our result i...
Nicolò Cesa-Bianchi, Claudio Gentile
CORR
2010
Springer
171views Education» more  CORR 2010»
13 years 2 months ago
Online Learning in Opportunistic Spectrum Access: A Restless Bandit Approach
We consider an opportunistic spectrum access (OSA) problem where the time-varying condition of each channel (e.g., as a result of random fading or certain primary users' activ...
Cem Tekin, Mingyan Liu
DAGM
2005
Springer
14 years 1 months ago
Rapid Online Learning of Objects in a Biologically Motivated Recognition Architecture
We present an approach for the supervised online learning of object representations based on a biologically motivated architecture of visual processing. We use the output of a rece...
Stephan Kirstein, Heiko Wersing, Edgar Körner
ICDM
2006
IEEE
119views Data Mining» more  ICDM 2006»
14 years 1 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 ...
EMNLP
2009
13 years 5 months ago
Multi-Class Confidence Weighted Algorithms
The recently introduced online confidence-weighted (CW) learning algorithm for binary classification performs well on many binary NLP tasks. However, for multi-class problems CW l...
Koby Crammer, Mark Dredze, Alex Kulesza