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ECML
2006
Springer
15 years 1 months ago
Constant Rate Approximate Maximum Margin Algorithms
We present a new class of perceptron-like algorithms with margin in which the "effective" learning rate, defined as the ratio of the learning rate to the length of the we...
Petroula Tsampouka, John Shawe-Taylor
ICDM
2010
IEEE
200views Data Mining» more  ICDM 2010»
14 years 6 months ago
Bayesian Maximum Margin Clustering
Abstract--Most well-known discriminative clustering models, such as spectral clustering (SC) and maximum margin clustering (MMC), are non-Bayesian. Moreover, they merely considered...
Bo Dai, Baogang Hu, Gang Niu
TKDE
2012
245views Formal Methods» more  TKDE 2012»
12 years 12 months ago
Semi-Supervised Maximum Margin Clustering with Pairwise Constraints
—The pairwise constraints specifying whether a pair of samples should be grouped together or not have been successfully incorporated into the conventional clustering methods such...
Hong Zeng, Yiu-ming Cheung
ESANN
2007
14 years 11 months ago
A metamorphosis of Canonical Correlation Analysis into multivariate maximum margin learning
Abstract. Canonical Correlation Analysis(CCA) is a useful tool to discover relationship between different sources of information represented by vectors. The solution of the underl...
Sándor Szedmák, Tijl De Bie, David R...
ESANN
2006
14 years 11 months ago
Synthesis of maximum margin and multiview learning using unlabeled data
In this presentation we show the semi-supervised learning with two input sources can be transformed into a maximum margin problem to be similar to a binary SVM. Our formulation exp...
Sándor Szedmák, John Shawe-Taylor