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Large-Margin Metric Learning for Partitioning Problems
Large-Margin Metric Learning Partitioning Problems
2013/4/28
In this paper, we consider unsupervised partitioning problems, such as clustering, image segmentation, video segmentation and other change-point detection problems. We focus on partitioning problems b...
Multiway Spectral Clustering: A Margin-Based Perspective
Spectral clustering spectral relaxation graph partitioning reproducing kernel Hilbert space large-margin classifi ca-tion Gaussian intrinsic autoregression
2011/3/22
Spectral clustering is a broad class of clustering procedures in which an intractable combinatorial optimization formulation of clustering is "relaxed" into a tractable eigenvector problem, and in whi...
Multiway Spectral Clustering: A Margin-Based Perspective
Spectral clustering spectral relaxation graph partitioning reproducing kernel Hilbert space large-margin classifi ca-tion Gaussian intrinsic autoregression
2011/3/23
Spectral clustering is a broad class of clustering procedures in which an intractable combinatorial optimization formulation of clustering is "relaxed" into a tractable eigenvector problem, and in whi...
Generalization error for multi-class margin classification
Convex and nonconvex losses import vector machines $psi$-learning sparse learning support vector machines
2009/9/16
In this article, we study rates of convergence of the generalization error of multi-class margin classifiers. In particular, we develop an upper bound theory quantifying the generalization error of va...
Risk Bounds for Classification Trees under a Margin Condition
Classification CART Pruning Margin Risk Bounds
2010/3/18
Risk bounds for Classification and Regression Trees (CART, Breiman et. al. 1984)
classifiers are obtained under a margin condition in the binary supervised classification
framework. These risk bound...