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» Complexity Measures of Supervised Classification Problems
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CORR
2010
Springer
101views Education» more  CORR 2010»
13 years 9 months ago
Online Learning: Random Averages, Combinatorial Parameters, and Learnability
We develop a theory of online learning by defining several complexity measures. Among them are analogues of Rademacher complexity, covering numbers and fatshattering dimension fro...
Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari
PRL
2006
98views more  PRL 2006»
13 years 9 months ago
Data complexity assessment in undersampled classification of high-dimensional biomedical data
Regularized linear classifiers have been successfully applied in undersampled, i.e. small sample size/high dimensionality biomedical classification problems. Additionally, a desig...
Richard Baumgartner, Ray L. Somorjai
BMCBI
2010
224views more  BMCBI 2010»
13 years 10 months ago
An adaptive optimal ensemble classifier via bagging and rank aggregation with applications to high dimensional data
Background: Generally speaking, different classifiers tend to work well for certain types of data and conversely, it is usually not known a priori which algorithm will be optimal ...
Susmita Datta, Vasyl Pihur, Somnath Datta
PAMI
2007
187views more  PAMI 2007»
13 years 9 months ago
Supervised Learning of Semantic Classes for Image Annotation and Retrieval
—A probabilistic formulation for semantic image annotation and retrieval is proposed. Annotation and retrieval are posed as classification problems where each class is defined as...
Gustavo Carneiro, Antoni B. Chan, Pedro J. Moreno,...
JMLR
2006
112views more  JMLR 2006»
13 years 9 months ago
Kernels on Prolog Proof Trees: Statistical Learning in the ILP Setting
We develop kernels for measuring the similarity between relational instances using background knowledge expressed in first-order logic. The method allows us to bridge the gap betw...
Andrea Passerini, Paolo Frasconi, Luc De Raedt