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» Boosting margin based distance functions for clustering
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RECOMB
2005
Springer
14 years 6 months ago
Predicting Protein-Peptide Binding Affinity by Learning Peptide-Peptide Distance Functions
Many important cellular response mechanisms are activated when a peptide binds to an appropriate receptor. In the immune system, the recognition of pathogen peptides begins when th...
Chen Yanover, Tomer Hertz
PRL
2007
118views more  PRL 2007»
13 years 5 months ago
Unifying multi-class AdaBoost algorithms with binary base learners under the margin framework
Multi-class AdaBoost algorithms AdaBooost.MO, -ECC and -OC have received a great attention in the literature, but their relationships have not been fully examined to date. In this...
Yijun Sun, Sinisa Todorovic, Jian Li
PAMI
2011
13 years 1 months ago
Semi-Supervised Learning via Regularized Boosting Working on Multiple Semi-Supervised Assumptions
—Semi-supervised learning concerns the problem of learning in the presence of labeled and unlabeled data. Several boosting algorithms have been extended to semi-supervised learni...
Ke Chen, Shihai Wang
IDA
2002
Springer
13 years 6 months ago
Boosting strategy for classification
This paper introduces a strategy for training ensemble classifiers by analysing boosting within margin theory. We present a bound on the generalisation error of ensembled classifi...
Huma Lodhi, Grigoris J. Karakoulas, John Shawe-Tay...
ICDM
2003
IEEE
71views Data Mining» more  ICDM 2003»
13 years 11 months ago
Tree-structured Partitioning Based on Splitting Histograms of Distances
We propose a novel clustering algorithm that is similar in spirit to classification trees. The data is recursively split using a criterion that applies a discrete curve evolution...
Longin Jan Latecki, Rajagopal Venugopal, Marc Sobe...