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» Data Mining via Support Vector Machines
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NIPS
2000
15 years 5 months ago
Vicinal Risk Minimization
The Vicinal Risk Minimization principle establishes a bridge between generative models and methods derived from the Structural Risk Minimization Principle such as Support Vector M...
Olivier Chapelle, Jason Weston, Léon Bottou...
131
Voted
NCA
2010
IEEE
15 years 2 months ago
Genetic algorithm-based training for semi-supervised SVM
The Support Vector Machine (SVM) is an interesting classifier with excellent power of generalization. In this paper, we consider applying the SVM to semi-supervised learning. We p...
Mathias M. Adankon, Mohamed Cheriet
CORR
2008
Springer
105views Education» more  CORR 2008»
15 years 4 months ago
Robust Machine Learning Applied to Terascale Astronomical Datasets
We present recent results from the LCDM3 collaboration between UIUC Astronomy and NCSA to deploy supercomputing cluster resources and machine learning algorithms for the mining of ...
Nicholas M. Ball, Robert J. Brunner, Adam D. Myers
KDD
2003
ACM
146views Data Mining» more  KDD 2003»
16 years 4 months ago
Style mining of electronic messages for multiple authorship discrimination: first results
This paper considers the use of computational stylistics for performing authorship attribution of electronic messages, addressing categorization problems with as many as 20 differ...
Shlomo Argamon, Marin Saric, Sterling Stuart Stein
KDD
2001
ACM
228views Data Mining» more  KDD 2001»
16 years 4 months ago
REVI-MINER, a KDD-environment for deviation detection and analysis of warranty and goodwill cost statements in automotive indust
REVI-MINER is a KDD-environment which supports the detection and analysis of deviations in warranty and goodwill cost statements. The system was developed within the framework of ...
Edgar Hotz, Udo Grimmer, W. Heuser, Gholamreza Nak...