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ICPR
2002
IEEE
16 years 8 months ago
The Combining Classifier: To Train or Not to Train?
When more than a single classifier has been trained for the same recognition problem the question arises how this set of classifiers may be combined into a final decision rule. Se...
Robert P. W. Duin
ICPR
2002
IEEE
16 years 8 months ago
Prototype Selection for Finding Efficient Representations of Dissimilarity Data
The nearest neighbor (NN) rule is a simple and intuitive method for solving classification problems. Originally, it uses distances to the complete training set. It performs well, ...
Elzbieta Pekalska, Robert P. W. Duin
ICPR
2002
IEEE
16 years 8 months ago
A Theory of the Quasi-Static World
We present the theory behind a novel unsupervised method for discovering quasi-static objects, objects that are stationary during some interval of observation, within image sequen...
Brandon C. S. Sanders, Randal C. Nelson, Rahul Suk...
ICML
2009
IEEE
16 years 8 months ago
Proximal regularization for online and batch learning
Many learning algorithms rely on the curvature (in particular, strong convexity) of regularized objective functions to provide good theoretical performance guarantees. In practice...
Chuong B. Do, Quoc V. Le, Chuan-Sheng Foo
ICML
2007
IEEE
16 years 8 months ago
Online discovery of similarity mappings
We consider the problem of choosing, sequentially, a map which assigns elements of a set A to a few elements of a set B. On each round, the algorithm suffers some cost associated ...
Alexander Rakhlin, Jacob Abernethy, Peter L. Bartl...