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SDM
2012
SIAM
216views Data Mining» more  SDM 2012»
13 years 6 months ago
Feature Selection "Tomography" - Illustrating that Optimal Feature Filtering is Hopelessly Ungeneralizable
:  Feature Selection “Tomography” - Illustrating that Optimal Feature Filtering is Hopelessly Ungeneralizable George Forman HP Laboratories HPL-2010-19R1 Feature selection; ...
George Forman
IDA
2000
Springer
15 years 3 months ago
Reducing redundancy in characteristic rule discovery by using integer programming techniques
The discovery of characteristic rules is a well-known data mining task and has lead to several successful applications. However, because of the descriptive nature of characteristic...
Tom Brijs, Koen Vanhoof, Geert Wets
171
Voted
KDD
2008
ACM
137views Data Mining» more  KDD 2008»
16 years 4 months ago
Learning classifiers from only positive and unlabeled data
The input to an algorithm that learns a binary classifier normally consists of two sets of examples, where one set consists of positive examples of the concept to be learned, and ...
Charles Elkan, Keith Noto
KDD
2005
ACM
153views Data Mining» more  KDD 2005»
16 years 4 months ago
Improving discriminative sequential learning with rare--but--important associations
Discriminative sequential learning models like Conditional Random Fields (CRFs) have achieved significant success in several areas such as natural language processing, information...
Xuan Hieu Phan, Minh Le Nguyen, Tu Bao Ho, Susumu ...
132
Voted
KDD
2004
ACM
124views Data Mining» more  KDD 2004»
16 years 4 months ago
Automatic multimedia cross-modal correlation discovery
Given an image (or video clip, or audio song), how do we automatically assign keywords to it? The general problem is to find correlations across the media in a collection of multi...
Jia-Yu Pan, Hyung-Jeong Yang, Christos Faloutsos, ...