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The aim of this paper is to show that one can achieve convergence rates of $N^{-\alpha+ \delta}$ for $\alpha > 1/2$ (and for $\delta > 0$ arbitrarily small) for nonperiodic $\alpha$-smooth cosine series using lattice rules without random…

Numerical Analysis · Mathematics 2012-11-19 Josef Dick , Dirk Nuyens , Friedrich Pillichshammer

We propose a computationally intensive method, the random lasso method, for variable selection in linear models. The method consists of two major steps. In step 1, the lasso method is applied to many bootstrap samples, each using a set of…

Applications · Statistics 2011-04-19 Sijian Wang , Bin Nan , Saharon Rosset , Ji Zhu

Maximum likelihood estimation furnishes powerful insights into voting theory, and the design of voting rules. However the MLE can usually be badly corrupted by a single outlying sample. This means that a single voter or a group of colluding…

Data Structures and Algorithms · Computer Science 2022-07-19 Allen Liu , Ankur Moitra

We study the locally recoverable codes on algebraic curves. In the first part of this article, we provide a bound of generalized Hamming weight of these codes. Whereas in the second part, we propose a new family of algebraic geometric LRC…

Commutative Algebra · Mathematics 2016-05-25 Edoardo Ballico , Chiara Marcolla

Encoding and indexing of lattice codes is generalized from self-similar lattice codes to a broader class of lattices. If coding lattice $\Lambda_{\textrm{c}}$ and shaping lattice $\Lambda_{\textrm{s}}$ satisfy $\Lambda_{\textrm{s}}…

Information Theory · Computer Science 2016-07-14 Brian M. Kurkoski

We propose and analyse randomized cubature formulae for the numerical integration of functions with respect to a given probability measure $\mu$ defined on a domain $\Gamma \subseteq \mathbb{R}^d$, in any dimension $d$. Each cubature…

Numerical Analysis · Mathematics 2020-12-04 Giovanni Migliorati , Fabio Nobile

Dependence of $a/r_c$ (inverse Sommer parameter in units of lattice spacing $a$) on $am_q$ (quark mass in lattice unit) has been observed in all lattice QCD simulations with sea quarks including the ones with improved actions. How much of…

High Energy Physics - Lattice · Physics 2008-03-11 Asit K. De , A. Harindranath , Jyotirmoy Maiti

Cellwise outliers are widespread in data and traditional robust methods may fail when applied to datasets under such contamination. We propose a variable selection procedure, that uses a pairwise robust estimator to obtain an initial…

Methodology · Statistics 2023-09-06 Peng Su , Garth Tarr , Samuel Muller

The realization of scalable fault-tolerant quantum computing is expected to hinge on quantum error-correcting codes. In the quest for more efficient quantum fault tolerance, a critical code parameter is the weight of measurements that…

Quantum Physics · Physics 2025-02-21 Austin Yubo He , Zi-Wen Liu

Kernel quadratures and other kernel-based approximation methods typically suffer from prohibitive cubic time and quadratic space complexity in the number of function evaluations. The problem arises because a system of linear equations needs…

Numerical Analysis · Mathematics 2018-01-09 Toni Karvonen , Simo Särkkä

A significant component of the cost of making predictions from lattice QCD stems from the computation of correlation functions on a given ensemble of gauge fields. This cost depends on the observable of interest and the details of its…

High Energy Physics - Lattice · Physics 2026-05-04 Tim Harris

We consider the problem of analyzing and designing gradient-based discrete-time optimization algorithms for a class of unconstrained optimization problems having strongly convex objective functions with Lipschitz continuous gradient. By…

Optimization and Control · Mathematics 2025-10-20 Simon Michalowsky , Carsten Scherer , Christian Ebenbauer

We study the approximation of integrals $\int_D f(\boldsymbol{x}^\top A) \mathrm{d} \mu(\boldsymbol{x})$, where $A$ is a matrix, by quasi-Monte Carlo (QMC) rules $N^{-1} \sum_{k=0}^{N-1} f(\boldsymbol{x}_k^\top A)$. We are interested in…

Numerical Analysis · Mathematics 2023-05-22 Josef Dick , Adrian Ebert , Lukas Herrmann , Peter Kritzer , Marcello Longo

Recall that Janson showed that if the edges of the complete graph $K_n$ are assigned exponentially distributed independent random weights, then the expected length of a shortest path between a fixed pair of vertices is asymptotically equal…

Combinatorics · Mathematics 2021-06-01 Alan Frieze , Wesley Pegden , Gregory Sorkin , Tomasz Tkocz

We consider the problem of robust and adaptive model predictive control (MPC) of a linear system, with unknown parameters that are learned along the way (adaptive), in a critical setting where failures must be prevented (robust). This…

Machine Learning · Computer Science 2020-10-22 Edouard Leurent , Denis Efimov , Odalric-Ambrym Maillard

This paper studies the robustness of reinforcement learning algorithms to errors in the learning process. Specifically, we revisit the benchmark problem of discrete-time linear quadratic regulation (LQR) and study the long-standing open…

Optimization and Control · Mathematics 2021-03-16 Bo Pang , Zhong-Ping Jiang

The purpose of this paper is to study convex bodies $C$ for which there exists no convex body $C^\prime\subsetneq C$ of the same lattice width. Such bodies shall be called ``lattice reduced'', and they occur naturally in the study of the…

Metric Geometry · Mathematics 2024-07-23 Giulia Codenotti , Ansgar Freyer

We construct random metric spaces by gluing together an infinite sequence of pointed metric spaces that we call blocks. At each step, we glue the next block to the structure constructed so far by randomly choosing a point on the structure…

Probability · Mathematics 2019-04-17 Delphin Sénizergues

We consider random lattice triangulations of $n\times k$ rectangular regions with weight $\lambda^{|\sigma|}$ where $\lambda>0$ is a parameter and $|\sigma|$ denotes the total edge length of the triangulation. When $\lambda\in(0,1)$ and $k$…

Probability · Mathematics 2015-05-25 Pietro Caputo , Fabio Martinelli , Alistair Sinclair , Alexandre Stauffer

We show that kernel-based quadrature rules for computing integrals can be seen as a special case of random feature expansions for positive definite kernels, for a particular decomposition that always exists for such kernels. We provide a…

Machine Learning · Computer Science 2015-11-10 Francis Bach