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Establishing optimal cut-offs for clinical biomarkers is a fundamental statistical problem in epidemiology, clinical trials, and drug discovery. While there is extensive literature regarding the definition of optimal cut-offs for scalar…

Methodology · Statistics 2025-03-11 Oscar Lado-Baleato , Carla Díaz-Louza , Francisco Gude , Marcos Matabuena

We present a framework for discriminative sequence classification where the learner works directly in the high dimensional predictor space of all subsequences in the training set. This is possible by employing a new coordinate-descent…

Machine Learning · Computer Science 2010-08-04 Georgiana Ifrim , Carsten Wiuf

We propose a family of near-metrics based on local graph diffusion to capture similarity for a wide class of data sets. These quasi-metametrics, as their names suggest, dispense with one or two standard axioms of metric spaces, specifically…

Machine Learning · Statistics 2017-10-18 Chu Wang , Iraj Saniee , William S. Kennedy , Chris A. White

A new approach is suggested to quantum differential calculus on certain quantum varieties. It consists in replacing quantum de Rham complexes with differentials satisfying Leibniz rule by those which are in a sense close to Koszul complexes…

Quantum Algebra · Mathematics 2008-11-26 P. Akueson , D. Gurevich

Image cropping is essential in image editing for obtaining a compositionally enhanced image. In display media, image cropping is a prospective technique for automatically creating media content. However, image cropping for media contents is…

Computer Vision and Pattern Recognition · Computer Science 2023-10-16 Takumi Nishiyasu , Wataru Shimoda , Yoichi Sato

Recent advances in the theory of metric measures spaces on the one hand, and of sub-Riemannian ones on the other hand, suggest the possibility of a "great unification" of Riemannian and sub-Riemannian geometries in a comprehensive framework…

Differential Geometry · Mathematics 2026-03-09 Davide Barilari , Andrea Mondino , Luca Rizzi

In recent years, manifold learning has become increasingly popular as a tool for performing non-linear dimensionality reduction. This has led to the development of numerous algorithms of varying degrees of complexity that aim to recover man…

Machine Learning · Statistics 2013-06-03 Dominique Perraul-Joncas , Marina Meila

The aim of this paper is to generalize the algorithm to compute jumping numbers on rational surfaces described in [AAD14] to varieties of dimension at least 3. Therefore, we introduce the notion of $\pi$-antieffective divisors, generalizing…

Algebraic Geometry · Mathematics 2016-03-03 Hans Baumers , Ferran Dachs-Cadefau

We provide a general contractibility criterion for subsets of Riemannian metrics on the disc. For instance, this result applies to the space of metrics that have positive Gauss curvature and make the boundary circle convex (or geodesic).…

Differential Geometry · Mathematics 2020-01-13 Alessandro Carlotto , Damin Wu

Metric learning aims to embed one metric space into another to benefit tasks like classification and clustering. Although a greatly distorted metric space has a high degree of freedom to fit training data, it is prone to overfitting and…

Machine Learning · Computer Science 2015-05-12 Renjie Liao , Jianping Shi , Ziyang Ma , Jun Zhu , Jiaya Jia

In this paper we introduce a general theory for nonlinear sufficient dimension reduction, and explore its ramifications and scope. This theory subsumes recent work employing reproducing kernel Hilbert spaces, and reveals many parallels…

Statistics Theory · Mathematics 2013-04-03 Kuang-Yao Lee , Bing Li , Francesca Chiaromonte

We present a new approach to rigid-body motion segmentation from two views. We use a previously developed nonlinear embedding of two-view point correspondences into a 9-dimensional space and identify the different motions by segmenting…

Computer Vision and Pattern Recognition · Computer Science 2014-06-25 Bryan Poling , Gilad Lerman

In image set classification, a considerable advance has been made by modeling the original image sets by second order statistics or linear subspace, which typically lie on the Riemannian manifold. Specifically, they are Symmetric Positive…

Computer Vision and Pattern Recognition · Computer Science 2018-05-31 Rui Wang , Xiao-Jun Wu , Kai-Xuan Chen , Josef Kittler

We develop a theory of $n \times n$-matrix Riemann-Hilbert problems for a class of jump contours and jump matrices of low regularity. Our basic assumption is that the contour $\Gamma$ is a finite union of simple closed Carleson curves in…

Complex Variables · Mathematics 2014-02-19 Jonatan Lenells

This paper provides a strategy to analyse the convergence of nonlinear analogues of linear subdivision processes on the sphere. In contrast to previous work, we study the Riemannian analogue of a linear scheme on a Riemannian manifold with…

Numerical Analysis · Mathematics 2020-01-28 Svenja Hüning , Johannes Wallner

We study the generalization performance of unregularized gradient methods for separable linear classification. While previous work mostly deal with the binary case, we focus on the multiclass setting with $k$ classes and establish novel…

Machine Learning · Computer Science 2025-05-29 Matan Schliserman , Tomer Koren

In this paper, we present a multigrid preconditioner for solving the linear system arising from the piecewise linear nonconforming Crouzeix-Raviart discretization of second order elliptic problems with jump coefficients. The preconditioner…

Numerical Analysis · Mathematics 2011-07-13 Blanca Ayuso De Dios , Michael Holst , Yunrong Zhu , Ludmil Zikatanov

We prove new versions of the isomorphic Busemann-Petty problem for two different measures and show how these results can be used to recover slicing and distance inequalities. We also prove a sharp upper estimate for the outer volume ratio…

Functional Analysis · Mathematics 2019-12-03 Alexander Koldobsky , Grigoris Paouris , Artem Zvavitch

Human similarity judgments are inconsistent with Euclidean, Hamming, Mahalanobis, and the majority of measures used in the extensive literatures on similarity and dissimilarity. From intrinsic properties of brain circuitry, we derive…

Neurons and Cognition · Quantitative Biology 2017-09-27 Antonio M Rodriguez , Richard Granger

We prove a general criterion for a metric space to have conformal dimension one. The conditions are stated in terms of the existence of enough local cut points in the space. We then apply this criterion to the boundaries of hyperbolic…

Metric Geometry · Mathematics 2013-11-05 Matias Carrasco Piaggio
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