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The problem of learning a correspondence relationship between nodes of two networks has drawn much attention of the computer science community and recently that of statisticians. The unseeded version of this problem, in which we do not know…

Methodology · Statistics 2018-08-24 Yuan Zhang

Recently, distributed dual averaging has received increasing attention due to its superiority in handling constraints and dynamic networks in multiagent optimization. However, all distributed dual averaging methods reported so far…

Optimization and Control · Mathematics 2020-03-20 Changxin Liu , Huiping Li , Yang Shi

This article concerns tests for the two-sample location problem when the dimension is larger than the sample size. The traditional multivariate-rank-based procedures cannot be used in high dimensional settings because the sample scatter…

Methodology · Statistics 2015-06-30 Long Feng

In this paper we study two geometric data structure problems in the special case when input objects or queries are fat rectangles. We show that in this case a significant improvement compared to the general case can be achieved. We describe…

Data Structures and Algorithms · Computer Science 2019-05-08 Timothy M. Chan , Yakov Nekrich , Michiel Smid

In contrast to set-point tracking which aims to reduce the tracking error between the tracker and the reference, tracking-in-range problems only focus on whether the tracker is within a given range around the reference, making it more…

Systems and Control · Electrical Eng. & Systems 2024-03-06 Nikilesh Ramesh , Eric C. Kerrigan , Yuanbo Nie

In this paper, we propose second-order sufficient optimality conditions for a very general nonconvex constrained optimization problem, which covers many prominent mathematical programs.Unlike the existing results in the literature, our…

Optimization and Control · Mathematics 2022-11-24 Matus Benko , Helmut Gfrerer , Jane Ye , Jin Zhang , Jinchuan Zhou

Given an Orthogonal Array we analyze the aberrations of the sub-fractions which are obtained by the deletion of some of its points. We provide formulae to compute the Generalized Word-Length Pattern of any sub-fraction. In the case of the…

Statistics Theory · Mathematics 2018-09-12 Roberto Fontana , Fabio Rapallo

We formulate a supervised learning problem, referred to as continuous ranking, where a continuous real-valued label Y is assigned to an observable r.v. X taking its values in a feature space $\mathcal{X}$ and the goal is to order all…

Machine Learning · Statistics 2018-01-18 Stephan Clémençon , Mastane Achab

Meaningful comparison between sets of observations often necessitates alignment or registration between them, and the resulting optimization problems range in complexity from those admitting simple closed-form solutions to those requiring…

Methodology · Statistics 2025-10-08 Hajg Jasa , Ronny Bergmann , Christian Kümmerle , Avanti Athreya , Zachary Lubberts

The variation of spectral subspaces for linear self-adjoint operators under an additive bounded off-diagonal perturbation is studied. To this end, the optimization approach for general perturbations in [J. Anal. Math., to appear;…

Spectral Theory · Mathematics 2016-07-28 Albrecht Seelmann

Orthogonal Arrays allow us to test various levels of each factor and balance the different factors so that we can estimate interactions as well as first order effects. There is a trade-off between how well we can sample different levels of…

Methodology · Statistics 2016-01-26 Joel Atkins , David B. Zax

This paper addresses two classes of different, yet interrelated optimization problems. The first class of problems involves a robot that must locate a hidden target in an environment that consists of a set of concurrent rays. The second…

Artificial Intelligence · Computer Science 2015-04-28 Spyros Angelopoulos

Unsupervised aggregation of independently built univariate predictors is explored as an alternative regularization approach for noisy, sparse datasets. Bipartite ranking algorithm Smooth Rank implementing this approach is introduced. The…

Machine Learning · Computer Science 2011-12-12 Marina Sapir

In this manuscript, we study stochastic comparisons of the second-order statistics from dependent or independent observations with modified proportional hazard rates models. First, we establish the usual stochastic order of the second-order…

Statistics Theory · Mathematics 2022-01-06 Niu Jiale

We investigate the relevance of time ordering in the definition of off-diagonal parton distributions in terms of products of fields. The method we use easily allows determination of their support properties and provides a link to their…

High Energy Physics - Phenomenology · Physics 2009-10-31 M. Diehl , T. Gousset

In this work, we propose a high-order multiscale method for an elliptic model problem with rough and possibly highly oscillatory coefficients. Convergence rates of higher order are obtained using the regularity of the right-hand side only.…

Numerical Analysis · Mathematics 2023-04-18 Zhaonan Dong , Moritz Hauck , Roland Maier

Ranking problems, also known as preference learning problems, define a widely spread class of statistical learning problems with many applications, including fraud detection, document ranking, medicine, credit risk screening, image ranking…

Machine Learning · Computer Science 2020-12-17 Tino Werner

This article addresses the problem of multi-object tracking by using a non-deterministic model of target behaviors with hard constraints. To capture the evolution of target features as well as their locations, we permit objects to lie in a…

Dynamical Systems · Mathematics 2024-01-23 Michael Robinson , Michael Stein , Henry S. Owen

We consider the problem of exact synchronization of two rankings at remote locations connected by a two-way channel. Such synchronization problems arise when items in the data are distinguishable, as is the case for playlists, tasklists,…

Information Theory · Computer Science 2014-02-13 Lili Su , Olgica Milenkovic

We highlight a striking difference in behavior between two widely used variants of coordinate ascent variational inference: the sequential and parallel algorithms. While such differences were known in the numerical analysis literature in…

Machine Learning · Statistics 2026-03-24 Debdeep Pati