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» Data mining, Hypergraph Transversals, and Machine Learning
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PKDD
2010
Springer
164views Data Mining» more  PKDD 2010»
14 years 7 months ago
Complexity Bounds for Batch Active Learning in Classification
Active learning [1] is a branch of Machine Learning in which the learning algorithm, instead of being directly provided with pairs of problem instances and their solutions (their l...
Philippe Rolet, Olivier Teytaud
CIKM
2009
Springer
15 years 4 months ago
L2 norm regularized feature kernel regression for graph data
Features in many real world applications such as Cheminformatics, Bioinformatics and Information Retrieval have complex internal structure. For example, frequent patterns mined fr...
Hongliang Fei, Jun Huan
ICML
2006
IEEE
15 years 10 months ago
Robust probabilistic projections
Principal components and canonical correlations are at the root of many exploratory data mining techniques and provide standard pre-processing tools in machine learning. Lately, p...
Cédric Archambeau, Michel Verleysen, Nicola...
SDM
2012
SIAM
216views Data Mining» more  SDM 2012»
13 years 4 days 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
SIGCSE
2006
ACM
163views Education» more  SIGCSE 2006»
15 years 3 months ago
TextMOLE: text mining operations library and environment
The paper describes the first version of the TextMOLE (Text Mining Operations Library and Environment) system for textual data mining. Currently TextMOLE acts as an advanced inde...
Daniel B. Waegel, April Kontostathis