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» Boosting margin based distance functions for clustering
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RECOMB
2005
Springer
14 years 5 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 4 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
12 years 11 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 4 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 10 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...