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We study the multi-objective minimum weight base problem, an abstraction of classical NP-hard combinatorial problems such as the multi-objective minimum spanning tree problem. We prove some important properties of the convex hull of the…

Artificial Intelligence · Computer Science 2023-06-07 Anh Viet Do , Aneta Neumann , Frank Neumann , Andrew M. Sutton

This paper studies methods for testing and estimating change-points in the covariance structure of a high-dimensional linear time series. The assumed framework allows for a large class of multivariate linear processes (including vector…

Statistics Theory · Mathematics 2020-01-14 Ansgar Steland

We study the problem of space and time efficient evaluation of a nonparametric estimator that approximates an unknown density. In the regime where consistent estimation is possible, we use a piecewise multivariate polynomial interpolation…

Statistics Theory · Mathematics 2020-11-11 Paxton Turner , Jingbo Liu , Philippe Rigollet

An estimation method is presented for polynomial phase signals, i.e., those adopting the form of a complex exponential whose phase is polynomial in its indices. Transcending the scope of existing techniques, the proposed estimator can…

Signal Processing · Electrical Eng. & Systems 2024-11-12 Heedong Do , Namyoon Lee , Angel Lozano

We survey and unify recent results on the existence of accurate algorithms for evaluating multivariate polynomials, and more generally for accurate numerical linear algebra with structured matrices. By "accurate" we mean that the computed…

Numerical Analysis · Mathematics 2008-05-21 James Demmel , Ioana Dumitriu , Olga Holtz , Plamen Koev

We develop algorithms for detecting multiple changepoints in functional data when the number of changepoints is unknown (unsupervised case), when it is specified apriori (supervised case), and when certain bounds are available…

Methodology · Statistics 2025-11-19 Sourav Chakrabarty , Anirvan Chakraborty , Shyamal K. De

We study the problem of {\em list-decodable mean estimation} for bounded covariance distributions. Specifically, we are given a set $T$ of points in $\mathbb{R}^d$ with the promise that an unknown $\alpha$-fraction of points in $T$, where…

Machine Learning · Computer Science 2020-06-23 Ilias Diakonikolas , Daniel M. Kane , Daniel Kongsgaard

Let $p$ be a prime. Given a polynomial in $\F_{p^m}[x]$ of degree $d$ over the finite field $\F_{p^m}$, one can view it as a map from $\F_{p^m}$ to $\F_{p^m}$, and examine the image of this map, also known as the value set. In this paper,…

Number Theory · Mathematics 2011-11-07 Qi Cheng , Joshua E. Hill , Daqing Wan

Polynomial optimization problems over binary variables can be expressed as integer programs using a linearization with extra monomials in addition to those arising in the given polynomial. We characterize when such a linearization yields an…

Discrete Mathematics · Computer Science 2020-05-18 Christopher Hojny , Marc E. Pfetsch , Matthias Walter

We consider the computation of syzygies of multivariate polynomials in a finite-dimensional setting: for a $\mathbb{K}[X_1,\dots,X_r]$-module $\mathcal{M}$ of finite dimension $D$ as a $\mathbb{K}$-vector space, and given elements…

Symbolic Computation · Computer Science 2020-06-22 Vincent Neiger , Éric Schost

We consider fast deterministic algorithms to identify the "best" linearly independent terms in multivariate mixtures and use them to compute, up to a user-selected accuracy, an equivalent representation with fewer terms. One algorithm…

Numerical Analysis · Mathematics 2019-02-20 Gregory Beylkin , Lucas Monzon , Xinshuo Yang

Consider a linear programming problem with n primal and m dual variables paired with n dual and m primal slack variables respectively, and aggregately denote these variables and slack variables as a vector z of length 2(n+m). Unlike…

Optimization and Control · Mathematics 2026-05-20 Wei Jing-Yuan

In this paper, we propose new deterministic and Monte Carlo interpolation algorithms for sparse multivariate polynomials represented by straight-line programs. Let $f$ be an $n$-variate polynomial given by a straight-line program, which has…

Symbolic Computation · Computer Science 2018-07-18 Qiao-Long Huang , Xiao-Shan Gao

This paper revisits the problem of computing empirical cumulative distribution functions (ECDF) efficiently on large, multivariate datasets. Computing an ECDF at one evaluation point requires $\mathcal{O}(N)$ operations on a dataset…

Data Structures and Algorithms · Computer Science 2021-09-21 Nicolas Langrené , Xavier Warin

In this paper, we consider non-convex multi-block bilevel optimization (MBBO) problems, which involve $m\gg 1$ lower level problems and have important applications in machine learning. Designing a stochastic gradient and controlling its…

Optimization and Control · Mathematics 2023-06-05 Quanqi Hu , Zi-Hao Qiu , Zhishuai Guo , Lijun Zhang , Tianbao Yang

In this article we provide an experimental algorithm that in many cases gives us an upper bound of the global infimum of a real polynomial on $\R^{n}$. It is very well known that to find the global infimum of a real polynomial on $\R^{n}$,…

Optimization and Control · Mathematics 2018-09-25 María López Quijorna

In this work we present a variant of the fast multipole method (FMM) for efficiently evaluating standard layer potentials on geometries with complex coordinates in two and three dimensions. The complex scaled boundary integral method for…

Numerical Analysis · Mathematics 2025-10-20 Tristan Goodwill , Leslie Greengard , Jeremy Hoskins , Manas Rachh , Yuguan Wang

The question how to certify non-negativity of a polynomial function lies at the heart of Real Algebra and also has important applications to Optimization. In this article we investigate the question of non-negativity in the context of…

Optimization and Control · Mathematics 2015-11-24 Paul Görlach , Cordian Riener , Tillmann Weißer

Statistical tests that compare classification algorithms are univariate and use a single performance measure, e.g., misclassification error, $F$ measure, AUC, and so on. In multivariate tests, comparison is done using multiple measures…

Machine Learning · Statistics 2014-09-17 Olcay Taner Yildiz , Ethem Alpaydin

Motivated by a connection with the factorization of multivariate polynomials, we study integral convex polytopes and their integral decompositions in the sense of the Minkowski sum. We first show that deciding decomposability of integral…

Combinatorics · Mathematics 2007-05-23 S. Gao , A. G. B. Lauder
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