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» Evaluating learning algorithms and classifiers
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111
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BMCBI
2006
111views more  BMCBI 2006»
15 years 16 days ago
PepDist: A New Framework for Protein-Peptide Binding Prediction based on Learning Peptide Distance Functions
Background: Many different aspects of cellular signalling, trafficking and targeting mechanisms are mediated by interactions between proteins and peptides. Representative examples...
Tomer Hertz, Chen Yanover
104
Voted
KDD
2008
ACM
181views Data Mining» more  KDD 2008»
16 years 27 days ago
Learning subspace kernels for classification
Kernel methods have been applied successfully in many data mining tasks. Subspace kernel learning was recently proposed to discover an effective low-dimensional subspace of a kern...
Jianhui Chen, Shuiwang Ji, Betul Ceran, Qi Li, Min...
167
Voted
KDD
2012
ACM
238views Data Mining» more  KDD 2012»
13 years 2 months ago
Multi-source learning for joint analysis of incomplete multi-modality neuroimaging data
Incomplete data present serious problems when integrating largescale brain imaging data sets from different imaging modalities. In the Alzheimer’s Disease Neuroimaging Initiativ...
Lei Yuan, Yalin Wang, Paul M. Thompson, Vaibhav A....
SAC
2006
ACM
15 years 6 months ago
The impact of sample reduction on PCA-based feature extraction for supervised learning
“The curse of dimensionality” is pertinent to many learning algorithms, and it denotes the drastic raise of computational complexity and classification error in high dimension...
Mykola Pechenizkiy, Seppo Puuronen, Alexey Tsymbal
ICML
2004
IEEE
16 years 1 months ago
Predictive automatic relevance determination by expectation propagation
In many real-world classification problems the input contains a large number of potentially irrelevant features. This paper proposes a new Bayesian framework for determining the r...
Yuan (Alan) Qi, Thomas P. Minka, Rosalind W. Picar...