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Submodular continuous functions are a category of (generally) non-convex/non-concave functions with a wide spectrum of applications. We characterize these functions and demonstrate that they can be maximized efficiently with approximation…

Machine Learning · Computer Science 2019-05-07 Andrew An Bian , Baharan Mirzasoleiman , Joachim M. Buhmann , Andreas Krause

Projecting fields between different meshes commonly arises in computational physics. This operation requires a supermesh construction and its computational cost is proportional to the number of cells of the supermesh $n$. Given any two…

Numerical Analysis · Mathematics 2023-01-10 M. Croci , P. E. Farrell

The problem of finding the minimizer of a sum of convex functions is central to the field of distributed optimization. Thus, it is of interest to understand how that minimizer is related to the properties of the individual functions in the…

Optimization and Control · Mathematics 2018-12-05 Kananart Kuwaranancharoen , Shreyas Sundaram

The main purpose of this paper is to prove that the point-line incidence bound due to Vinh (2011) over arbitrary finite fields can be improved in certain ranges by using tools from the VC-dimension theory. As consequences, a number of…

Combinatorics · Mathematics 2023-03-02 Alex Iosevich , Thang Pham , Steven Senger , Michael Tait

A method for computing lower bounds on capacities of 2-dimensional constraints having a symmetric presentation in either the horizontal or the vertical direction is presented. The method is a generalization of the method of Calkin and Wilf…

Information Theory · Computer Science 2009-03-11 Erez Louidor , Brian Marcus

Vertical decomposition is a widely used general technique for decomposing the cells of arrangements of semi-algebraic sets in ${{\mathbb R}}^d$ into constant-complexity subcells. In this paper, we settle in the affirmative a few…

Computational Geometry · Computer Science 2026-05-12 Pankaj K. Agarwal , Esther Ezra , Micha Sharir

We investigate inexact proximity operators for weakly convex functions. To this aim, we derive sum rules for proximal {\epsilon}-subdifferentials, by incorporating the moduli of weak convexity of the functions into the respective formulas.…

Optimization and Control · Mathematics 2024-04-24 Ewa Bednarczuk , Giovanni Bruccola , Gabriele Scrivanti , The Hung Tran

We derive a lower and upper bound on the reliability function of discrete memoryless multiple-access channel (MAC) with noiseless feedback and variable-length codes (VLCs). For the upper-bound, we use proof techniques of Burnashev for the…

Information Theory · Computer Science 2018-07-02 Mohsen Heidari , Achilleas Anastasopoulos , S. Sandeep Pradhan

Chapter 1 deals with the problem of the existence of an upper/lower envelope from a convex cone or, more generally, a convex set for functions on the projective limit of vector lattices with values in the completion of the Kantorovich space…

Functional Analysis · Mathematics 2018-12-31 B. N. Khabibullin , A. P. Rozit , E. B. Khabibullina

Recently, Gilmer proved the first constant lower bound for the union-closed sets conjecture via an information-theoretic argument. The heart of the argument is an entropic inequality involving the OR function of two i.i.d.\ binary vectors,…

Information Theory · Computer Science 2023-06-16 Jingbo Liu

We give a criterion for bounding the homological finiteness length of certain HF-groups. This is used in two distinct contexts. Firstly, the homological finiteness length of a non-uniform lattice on a locally finite n-dimensional…

Group Theory · Mathematics 2014-02-26 Giovanni Gandini

Given a bounded class of functions G and independent random variables X1, . . . , Xn, we provide an upper bound for the expectation of the supremum of the empirical process over elements of G having a small variance. Our bound applies in…

Probability · Mathematics 2015-09-08 Yannick Baraud

We present a method for finding lower bounds on the global infima of integral variational problems, wherein $\int_\Omega f(x,u(x),\nabla u(x)){\rm d}x$ is minimized over functions $u\colon\Omega\subset\mathbb{R}^n\to\mathbb{R}^m$ satisfying…

Optimization and Control · Mathematics 2023-08-15 Alexander Chernyavsky , Jason J. Bramburger , Giovanni Fantuzzi , David Goluskin

This paper presents a method to analyze the powers of a given trilinear form (a special kind of algebraic constructions also called a tensor) and obtain upper bounds on the asymptotic complexity of matrix multiplication. Compared with…

Data Structures and Algorithms · Computer Science 2021-10-05 François Le Gall

Support vector machine (SVM) has attracted great attentions for the last two decades due to its extensive applications, and thus numerous optimization models have been proposed. To distinguish all of them, in this paper, we introduce a new…

Optimization and Control · Mathematics 2021-04-06 Huajun Wang , Yuanhai Shao , Shenglong Zhou , Ce Zhang , Naihua Xiu

A proof for the lower bound is provided for the smallest eigenvalue of finite element equations with arbitrary conforming simplicial meshes. The bound has a similar form as the one by Graham and McLean [SIAM J. Numer. Anal., 44 (2006), pp.…

Numerical Analysis · Mathematics 2021-06-24 Lennard Kamenski

Using the translation method of Tartar, Murat, Lurie, and Cherkaev bounds are derived on the volume occupied by an inclusion in a three-dimensional conducting body. They assume electrical impedance tomography measurements have been made for…

Analysis of PDEs · Mathematics 2012-06-05 Hyeonbae Kang , Graeme W. Milton

This paper studies the lower bound complexity for the optimization problem whose objective function is the average of $n$ individual smooth convex functions. We consider the algorithm which gets access to gradient and proximal oracle for…

Optimization and Control · Mathematics 2019-08-23 Guangzeng Xie , Luo Luo , Zhihua Zhang

We give the sharp lower bound of the volume product of $n$-dimensional convex bodies which are invariant under a discrete subgroup $SO(K)=\{ g \in SO(n); g(K)=K \}$, where $K$ is an $n$-cube or $n$-simplex. This provides new partial results…

Metric Geometry · Mathematics 2022-03-29 Hiroshi Iriyeh , Masataka Shibata

We define a reduction mechanism for LP and SDP formulations that degrades approximation factors in a controlled fashion. Our reduction mechanism is a minor restriction of classical reductions establishing inapproximability in the context of…

Computational Complexity · Computer Science 2016-01-20 Gábor Braun , Sebastian Pokutta , Daniel Zink