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In this paper we study local error bound moduli for a locally Lipschitz and regular function via its outer limiting subdifferential set. We show that the distance of 0 from the outer limiting subdifferential of the support function of the…

Optimization and Control · Mathematics 2016-08-12 Minghua Li , Kaiwen Meng , Xiaoqi Yang

We introduce new moduli of smoothness for functions $f\in L_p[-1,1]\cap C^{r-1}(-1,1)$, $1\le p\le\infty$, $r\ge1$, that have an $(r-1)$st locally absolutely continuous derivative in $(-1,1)$, and such that $\varphi^rf^{(r)}$ is in…

Classical Analysis and ODEs · Mathematics 2015-07-20 K. A. Kopotun , D. Leviatan , I. A. Shevchuk

We consider the problem of testing whether an unknown low-degree polynomial $p$ over $\mathbb{R}^n$ is sparse versus far from sparse, given access to noisy evaluations of the polynomial $p$ at \emph{randomly chosen points}. This is a…

Data Structures and Algorithms · Computer Science 2025-11-12 Yiqiao Bao , Anindya De , Shivam Nadimpalli , Rocco A. Servedio , Nathan White

We consider the problem of enumerating relevant features hidden in other irrelevant information for multi-labeled data, which is formalized as learning juntas. A $k$-junta function is a function which depends on only $k$ coordinates of the…

Machine Learning · Computer Science 2019-07-16 Mikito Nanashima

Submodular functions are a special class of set functions which naturally model the notion of representativeness, diversity, coverage etc. and have been shown to be computationally very efficient. A lot of past work has applied submodular…

Machine Learning · Computer Science 2022-02-24 Vishal Kaushal , Ganesh Ramakrishnan , Rishabh Iyer

The relative performance of competing point forecasts is usually measured in terms of loss or scoring functions. It is widely accepted that these scoring function should be strictly consistent in the sense that the expected score is…

Statistics Theory · Mathematics 2019-04-08 Tobias Fissler , Johanna F. Ziegel

We consider the problem of testing equality of functions $f_j:[0,1]\to \mathbb{R}$ for $j=1,2,...,J$ the basis of $J$ independent samples from possibly different distributions under the assumption that the functions are monotone. We provide…

Statistics Theory · Mathematics 2013-07-02 Cécile Durot , Piet Groeneboom , Hendrik P. Lopuhaä

The need for recognition/approximation of functions in terms of elementary functions/operations emerges in many areas of experimental mathematics, numerical analysis, computer algebra systems, model building, machine learning, approximation…

Discrete Mathematics · Computer Science 2021-06-09 Andrzej Odrzywolek

For a proper extended real-valued function, this work focuses on the relationship between the subregularity of its subdifferential mapping relative to the critical set and its KL property of exponent 1/2. When the function is lsc convex, we…

Optimization and Control · Mathematics 2019-10-01 Shaohua Pan , Yulan Liu

In the present paper we introduce and investigate an interesting subclass K_{s}^{(k)}({\gamma},p) of analytic and p-valently close-to-convex functions in the open unit disk U. For functions belonging to this class, we derive several…

Complex Variables · Mathematics 2016-12-28 Serap Bulut

This paper addresses the problem of sequential submodular maximization: selecting and ranking items in a sequence to optimize some composite submodular function. In contrast to most of the previous works, which assume access to the utility…

Machine Learning · Computer Science 2024-09-10 Jing Yuan , Shaojie Tang

We design sequential tests for a large class of nonparametric null hypotheses based on elicitable and identifiable functionals. Such functionals are defined in terms of scoring functions and identification functions, which are ideal…

Statistics Theory · Mathematics 2023-06-06 Philippe Casgrain , Martin Larsson , Johanna Ziegel

Hub importance scores in multilayer networks persist more strongly between functionally similar layers than dissimilar ones. We call this the Functional Proximity Law and test it across 23 pre-registered experiments: 13 canonical domains…

Social and Information Networks · Computer Science 2026-05-26 Vladi Ivanov

Call a function f : F_2^n -> {0,1} odd-cycle-free if there are no x_1, ..., x_k in F_2^n with k an odd integer such that f(x_1) = ... = f(x_k) = 1 and x_1 + ... + x_k = 0. We show that one can distinguish odd-cycle-free functions from those…

Data Structures and Algorithms · Computer Science 2012-07-16 Arnab Bhattacharyya , Elena Grigorescu , Prasad Raghavendra , Asaf Shapira

We use p-values as a discrepancy criterion for identifying the threshold value at which a regression function takes off from its baseline value -- a problem that is motivated by applications in omics experiments, systems engineering,…

Methodology · Statistics 2010-08-26 Bodhisattva Sen , Moulinath Banerjee , George Michialidis

We consider the problem of approximating and learning disjunctions (or equivalently, conjunctions) on symmetric distributions over $\{0,1\}^n$. Symmetric distributions are distributions whose PDF is invariant under any permutation of the…

Machine Learning · Computer Science 2015-05-27 Vitaly Feldman , Pravesh Kothari

In this note, we introduce the notion of modulus of $p$-variation for a function of a real variable, and show that it serves in at least two important problems, namely, the uniform convergence of Fourier series and computation of certain…

Functional Analysis · Mathematics 2020-11-17 Gholam Hossein Esslamzadeh , Milad Moazami Goodarzi , Mahdi Hormozi , Martin Lind

We give the first algorithm that is both query-efficient and time-efficient for testing whether an unknown function $f: \{0,1\}^n \to \{0,1\}$ is an $s$-sparse GF(2) polynomial versus $\eps$-far from every such polynomial. Our algorithm…

Computational Complexity · Computer Science 2008-05-14 Ilias Diakonikolas , Homin K. Lee , Kevin Matulef , Rocco A. Servedio , Andrew Wan

We study the $\ell_p$ regression problem, which requires finding $\mathbf{x}\in\mathbb R^{d}$ that minimizes $\|\mathbf{A}\mathbf{x}-\mathbf{b}\|_p$ for a matrix $\mathbf{A}\in\mathbb R^{n \times d}$ and response vector…

Data Structures and Algorithms · Computer Science 2022-03-16 Raphael A. Meyer , Cameron Musco , Christopher Musco , David P. Woodruff , Samson Zhou

A differentiable function is pseudoconvex if and only if its restrictions over straight lines are pseudoconvex. A differentiable function depending on one variable, defined on some closed interval $[a,b]$ is pseudoconvex if and only if…

Optimization and Control · Mathematics 2019-11-19 Vsevolod Ivanov Ivanov
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