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ICML
2004
IEEE
15 years 10 months ago
Large margin hierarchical classification
We present an algorithmic framework for supervised classification learning where the set of labels is organized in a predefined hierarchical structure. This structure is encoded b...
Ofer Dekel, Joseph Keshet, Yoram Singer
COLT
2000
Springer
15 years 2 months ago
PAC Analogues of Perceptron and Winnow via Boosting the Margin
We describe a novel family of PAC model algorithms for learning linear threshold functions. The new algorithms work by boosting a simple weak learner and exhibit complexity bounds...
Rocco A. Servedio
ICML
2004
IEEE
15 years 10 months ago
Hyperplane margin classifiers on the multinomial manifold
The assumptions behind linear classifiers for categorical data are examined and reformulated in the context of the multinomial manifold, the simplex of multinomial models furnishe...
Guy Lebanon, John D. Lafferty
ICML
2004
IEEE
15 years 10 months ago
Boosting margin based distance functions for clustering
The performance of graph based clustering methods critically depends on the quality of the distance function, used to compute similarities between pairs of neighboring nodes. In t...
Tomer Hertz, Aharon Bar-Hillel, Daphna Weinshall
ICML
2004
IEEE
15 years 10 months ago
Links between perceptrons, MLPs and SVMs
We propose to study links between three important classification algorithms: Perceptrons, Multi-Layer Perceptrons (MLPs) and Support Vector Machines (SVMs). We first study ways to...
Ronan Collobert, Samy Bengio