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» Support vector machine for functional data classification
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ICDM
2007
IEEE
97views Data Mining» more  ICDM 2007»
16 years 14 days ago
Supervised Learning by Training on Aggregate Outputs
Supervised learning is a classic data mining problem where one wishes to be be able to predict an output value associated with a particular input vector. We present a new twist on...
David R. Musicant, Janara M. Christensen, Jamie F....
146
Voted
ICDAR
2009
IEEE
16 years 27 days ago
Online Recognition of Multi-Stroke Symbols with Orthogonal Series
We propose an efficient method to recognize multi-stroke handwritten symbols. The method is based on computing the truncated Legendre-Sobolev expansions of the coordinate functio...
Oleg Golubitsky, Stephen M. Watt
160
Voted
PPSN
2010
Springer
15 years 4 months ago
Comparison-Based Optimizers Need Comparison-Based Surrogates
Abstract. Taking inspiration from approximate ranking, this paper investigates the use of rank-based Support Vector Machine as surrogate model within CMA-ES, enforcing the invarian...
Ilya Loshchilov, Marc Schoenauer, Michèle S...
177
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KDD
2003
ACM
214views Data Mining» more  KDD 2003»
16 years 6 months ago
Adaptive duplicate detection using learnable string similarity measures
The problem of identifying approximately duplicate records in databases is an essential step for data cleaning and data integration processes. Most existing approaches have relied...
Mikhail Bilenko, Raymond J. Mooney
BICOB
2009
Springer
15 years 10 months ago
A New Machine Learning Approach for Protein Phosphorylation Site Prediction in Plants
Protein phosphorylation is a crucial regulatory mechanism in various organisms. With recent improvements in mass spectrometry, phosphorylation site data are rapidly accumulating. D...
Jianjiong Gao, Ganesh Kumar Agrawal, Jay J. Thelen...