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IEEE Transactions on Neural Networks and Learning Systems, 2022
Margin is an important concept in machine learning; theoretical analyses further reveal that the distribution of margin plays a more critical role than the minimum margin in generalization power. Recently, several approaches have achieved performance breakthroughs by optimizing the margin distribution, but their computational cost, which is usually ...
Jun Wang, Zhi-Hua Zhou
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Margin is an important concept in machine learning; theoretical analyses further reveal that the distribution of margin plays a more critical role than the minimum margin in generalization power. Recently, several approaches have achieved performance breakthroughs by optimizing the margin distribution, but their computational cost, which is usually ...
Jun Wang, Zhi-Hua Zhou
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Boosting the Margin Distribution
Proceedings of the twelfth annual conference on Computational learning theory, 2000The paper considers applying a boosting strategy to optimise the generalisation bound obtained recently by Shawe-Taylor and Cristianini [7] in terms of the two norm of the slack variables. The formulation performs gradient descent over the quadratic loss function which is insensitive to points with a large margin. A novel feature of this algorithm is a
Huma Lodhi +2 more
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Optimal Margin Distribution Clustering
Proceedings of the AAAI Conference on Artificial Intelligence, 2018Maximum margin clustering (MMC), which borrows the large margin heuristic from support vector machine (SVM), has achieved more accurate results than traditional clustering methods. The intuition is that, for a good clustering, when labels are assigned to different clusters, SVM can achieve a large minimum margin on this data.
Teng Zhang 0001, Zhi-Hua Zhou
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On a Bivariate Distribution with Exponential Marginals
Scandinavian Journal of Statistics, 1999A new bivariate distribution with exponential marginals has been introduced by Singpurwalla & Youngren (1993). This distribution is absolutely continuous and has a single parameter. It was originally motivated as the failure model for a two‐component system experiencing damage described by a shot–noise process. The purpose of this paper is two‐fold.
Singpurwalla, Nozer D., Kotz, Samuel
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, 2014 Marginal distributions of genetic coalgebras
Journal of Mathematical Biology, 2013We consider the backward evolution of a particular type of Mendelian genetic system whose transition probabilities give place to the so-called coalgebras with genetic realization and describe the equilibrium states of such mathematical objects and therefore those of the genetic system. We exploit the relationship between the genetic coalgebras modeling
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