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» Experimental perspectives on learning from imbalanced data
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KDD
2007
ACM
149views Data Mining» more  KDD 2007»
14 years 8 months ago
Distributed classification in peer-to-peer networks
This work studies the problem of distributed classification in peer-to-peer (P2P) networks. While there has been a significant amount of work in distributed classification, most o...
Ping Luo, Hui Xiong, Kevin Lü, Zhongzhi Shi
ICML
2002
IEEE
14 years 8 months ago
Syllables and other String Kernel Extensions
During the last years, the use of string kernels that compare documents has been shown to achieve good results on text classification problems. In this paper we introduce the appl...
Craig Saunders, Hauke Tschach, John Shawe-Taylor
ALT
2008
Springer
14 years 4 months ago
Nonparametric Independence Tests: Space Partitioning and Kernel Approaches
Abstract. Three simple and explicit procedures for testing the independence of two multi-dimensional random variables are described. Two of the associated test statistics (L1, log-...
Arthur Gretton, László Györfi
WWW
2010
ACM
14 years 2 months ago
A scalable machine-learning approach for semi-structured named entity recognition
Named entity recognition studies the problem of locating and classifying parts of free text into a set of predefined categories. Although extensive research has focused on the de...
Utku Irmak, Reiner Kraft
IPSN
2010
Springer
14 years 2 months ago
Online distributed sensor selection
A key problem in sensor networks is to decide which sensors to query when, in order to obtain the most useful information (e.g., for performing accurate prediction), subject to co...
Daniel Golovin, Matthew Faulkner, Andreas Krause