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» Learning Rules from Distributed Data
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ICML
2006
IEEE
16 years 3 months ago
Nightmare at test time: robust learning by feature deletion
When constructing a classifier from labeled data, it is important not to assign too much weight to any single input feature, in order to increase the robustness of the classifier....
Amir Globerson, Sam T. Roweis
112
Voted
NIPS
2008
15 years 4 months ago
Unsupervised Learning of Visual Sense Models for Polysemous Words
Polysemy is a problem for methods that exploit image search engines to build object category models. Existing unsupervised approaches do not take word sense into consideration. We...
Kate Saenko, Trevor Darrell
ICS
2007
Tsinghua U.
15 years 8 months ago
Locality of sampling and diversity in parallel system workloads
Observing the workload on a computer system during a short (but not too short) time interval may lead to distributions that are significantly different from those that would be o...
Dror G. Feitelson
144
Voted
CIDM
2009
IEEE
15 years 9 months ago
A new hybrid method for Bayesian network learning With dependency constraints
Abstract— A Bayes net has qualitative and quantitative aspects: The qualitative aspect is its graphical structure that corresponds to correlations among the variables in the Baye...
Oliver Schulte, Gustavo Frigo, Russell Greiner, We...
117
Voted
PKDD
2001
Springer
168views Data Mining» more  PKDD 2001»
15 years 7 months ago
Identification of ECG Arrhythmias Using Phase Space Reconstruction
Changes in the normal rhythmicity of a human heart may result in different cardiac arrhythmias, which may be immediately fatal or cause irreparable damage to the heart when sustain...
Felice M. Roberts, Richard J. Povinelli, Kristina ...