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» Generation of Attributes for Learning Algorithms
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COLT
2005
Springer
13 years 10 months ago
Data Dependent Concentration Bounds for Sequential Prediction Algorithms
Abstract. We investigate the generalization behavior of sequential prediction (online) algorithms, when data are generated from a probability distribution. Using some newly develop...
Tong Zhang
SCCC
2000
IEEE
14 years 1 months ago
A Genetic Classifier Tool
Knowledge discovery is the most desirable end product of an enterprise information system. Researches from different areas recognize that a new generation of intelligent tools for...
Aurora T. R. Pozo, Mozart Hasse
MLDM
2010
Springer
13 years 3 months ago
Fast Algorithms for Constant Approximation k-Means Clustering
In this paper we study the k-means clustering problem. It is well-known that the general version of this problem is NP-hard. Numerous approximation algorithms have been proposed fo...
Mingjun Song, Sanguthevar Rajasekaran
UAI
2003
13 years 10 months ago
The Information Bottleneck EM Algorithm
Learning with hidden variables is a central challenge in probabilistic graphical models that has important implications for many real-life problems. The classical approach is usin...
Gal Elidan, Nir Friedman
ML
2000
ACM
105views Machine Learning» more  ML 2000»
13 years 8 months ago
Multiple Comparisons in Induction Algorithms
Abstract. A single mechanism is responsible for three pathologies of induction algorithms: attribute selection errors, overfitting, and oversearching. In each pathology, induction ...
David D. Jensen, Paul R. Cohen