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ECML
2006
Springer
13 years 9 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»
13 years 2 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»
11 years 7 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
13 years 6 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
13 years 6 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