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» Learning of Boolean Functions Using Support Vector Machines
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WWW
2008
ACM
14 years 8 months ago
Detecting image spam using visual features and near duplicate detection
Email spam is a much studied topic, but even though current email spam detecting software has been gaining a competitive edge against text based email spam, new advances in spam g...
Bhaskar Mehta, Saurabh Nangia, Manish Gupta 0002, ...
NIPS
2003
13 years 9 months ago
Max-Margin Markov Networks
In typical classification tasks, we seek a function which assigns a label to a single object. Kernel-based approaches, such as support vector machines (SVMs), which maximize the ...
Benjamin Taskar, Carlos Guestrin, Daphne Koller
COLT
2006
Springer
13 years 11 months ago
A Sober Look at Clustering Stability
Stability is a common tool to verify the validity of sample based algorithms. In clustering it is widely used to tune the parameters of the algorithm, such as the number k of clust...
Shai Ben-David, Ulrike von Luxburg, Dávid P...
FSKD
2007
Springer
98views Fuzzy Logic» more  FSKD 2007»
14 years 1 months ago
Learning Selective Averaged One-Dependence Estimators for Probability Estimation
Naïve Bayes is a well-known effective and efficient classification algorithm, but its probability estimation performance is poor. Averaged One-Dependence Estimators, simply AODE,...
Qing Wang, Chuan-hua Zhou, Jiankui Guo
ICML
2002
IEEE
14 years 8 months ago
Learning the Kernel Matrix with Semi-Definite Programming
Kernel-based learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is perfor...
Gert R. G. Lanckriet, Nello Cristianini, Peter L. ...