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ICML
2003
IEEE
16 years 7 months ago
Semi-Supervised Learning of Mixture Models
This paper analyzes the performance of semisupervised learning of mixture models. We show that unlabeled data can lead to an increase in classification error even in situations wh...
Fabio Gagliardi Cozman, Ira Cohen, Marcelo Cesar C...
ICANN
2009
Springer
15 years 11 months ago
Learning SVMs from Sloppily Labeled Data
This paper proposes a modelling of Support Vector Machine (SVM) learning to address the problem of learning with sloppy labels. In binary classification, learning with sloppy labe...
Guillaume Stempfel, Liva Ralaivola
160
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ICASSP
2011
IEEE
14 years 10 months ago
Detecting oscillating singularities in multifractal analysis: Application to hydrodynamic turbulence
Multifractal analysis describes data as a collection of singularities. However, its classical formulation does not account for their possibly oscillating nature, while, in a numbe...
Patrice Abry, Stéphane G. Roux, Stép...
BMCBI
2006
109views more  BMCBI 2006»
15 years 6 months ago
An integrated system for genetic analysis
Background: Large-scale genetic mapping projects require data management systems that can handle complex phenotypes and detect and correct high-throughput genotyping errors, yet a...
Simon Fiddy, David Cattermole, Dong Xie, Xiao Yuan...
PSB
2004
15 years 8 months ago
Modeling Cellular Processes with Variational Bayesian Cooperative Vector Quantizer
Gene expression of a cell is controlled by sophisticated cellular processes. The capability of inferring the states of these cellular processes would provide insight into the mech...
Xinghua Lu, Milos Hauskrecht, Roger S. Day