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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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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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Margin Distribution Bounds on Generalization
1999A number of results have bounded generalization of a classi fier in terms of its margin on the training points. There has been some debate about whether the minimum margin is the best measure of the distribution of training set margin values with which to estimate the generalization.
John Shawe-Taylor, Nello Cristianini
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A New Bivariate Distribution with Rayleigh and Lindley Distributions as Marginals
Journal of Statistical Theory and Practice, 2020zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Thomas, P. Yageen, Jose, Jitto
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Large Margin Distribution Learning
2014Support vector machines (SVMs) and Boosting are possibly the two most popular learning approaches during the past two decades. It is well known that the margin is a fundamental issue of SVMs, whereas recently the margin theory for Boosting has been defended, establishing a connection between these two mainstream approaches.
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Bounds on margin distributions inBlearningBproblems
Annales de l?Institut Henri Poincare (B) Probability and Statistics, 2003zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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A Reformulation of the Marginal Productivity Theory of Distribution
Econometrica, 1984Reformulating marginal productivity theory by replacing productivity with respect to commodities with productivity with respect to persons and then defining perfectly competitive equilibrium as an allocation at which each person receives the marginal product of his/her contribution - called a no-surplus allocation - there emerges a competitive theory ...
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