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CORR
2010
Springer
124views Education» more  CORR 2010»
15 years 6 months ago
Online Learning of Noisy Data with Kernels
We study online learning when individual instances are corrupted by adversarially chosen random noise. We assume the noise distribution is unknown, and may change over time with n...
Nicolò Cesa-Bianchi, Shai Shalev-Shwartz, O...
CORR
2006
Springer
127views Education» more  CORR 2006»
15 years 6 months ago
Semi-Supervised Learning -- A Statistical Physics Approach
We present a novel approach to semisupervised learning which is based on statistical physics. Most of the former work in the field of semi-supervised learning classifies the point...
Gad Getz, Noam Shental, Eytan Domany
CSCL
2007
114views more  CSCL 2007»
15 years 6 months ago
Community-based learning: The core competency of residential, research-based universities
Traditionally, universities focus primarily on instructionist teaching. Such an understanding has been criticized from theoretical and practical points of view. We believe that so...
Gerhard Fischer, Markus Rohde, Volker Wulf
NN
2006
Springer
153views Neural Networks» more  NN 2006»
15 years 6 months ago
An incremental network for on-line unsupervised classification and topology learning
This paper presents an on-line unsupervised learning mechanism for unlabeled data that are polluted by noise. Using a similarity thresholdbased and a local error-based insertion c...
Shen Furao, Osamu Hasegawa
ISCI
2007
170views more  ISCI 2007»
15 years 6 months ago
Automatic learning of cost functions for graph edit distance
Graph matching and graph edit distance have become important tools in structural pattern recognition. The graph edit distance concept allows us to measure the structural similarit...
Michel Neuhaus, Horst Bunke