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Many convex problems in machine learning and computer science share the same form: \begin{align*} \min_{x} \sum_{i} f_i( A_i x + b_i), \end{align*} where $f_i$ are convex functions on $\mathbb{R}^{n_i}$ with constant $n_i$, $A_i \in…

Data Structures and Algorithms · Computer Science 2019-05-14 Yin Tat Lee , Zhao Song , Qiuyi Zhang

We consider a stochastic version of the proximal point algorithm for optimization problems posed on a Hilbert space. A typical application of this is supervised learning. While the method is not new, it has not been extensively analyzed in…

Optimization and Control · Mathematics 2021-09-28 Monika Eisenmann , Tony Stillfjord , Måns Williamson

We consider box-constrained integer programs with objective $g(Wx) + c^T x$, where $g$ is a "complicated" function with an $m$ dimensional domain. Here we assume we have $n \gg m$ variables and that $W \in \mathbb Z^{m \times n}$ is an…

Data Structures and Algorithms · Computer Science 2023-03-07 Daniel Dadush , Arthur Léonard , Lars Rohwedder , José Verschae

This paper presents computationally feasible rank-one relaxation algorithms for the efficient simulation of a time-incremental damage model with nonconvex incremental stress potentials in multiple spatial dimensions. While the standard…

Computational Engineering, Finance, and Science · Computer Science 2023-02-10 Daniel Balzani , Maximilian Köhler , Timo Neumeier , Malte A. Peter , Daniel Peterseim

Several algorithms with an approximation guarantee of $O(\log n)$ are known for the Set Cover problem, where $n$ is the number of elements. We study a generalization of the Set Cover problem, called the Partition Set Cover problem. Here,…

Data Structures and Algorithms · Computer Science 2018-12-04 Tanmay Inamdar , Kasturi Varadarajan

We study the problem of sampling an approximately uniformly random satisfying assignment for atomic constraint satisfaction problems i.e. where each constraint is violated by only one assignment to its variables. Let $p$ denote the maximum…

Data Structures and Algorithms · Computer Science 2021-02-17 Vishesh Jain , Huy Tuan Pham , Thuy-Duong Vuong

The goal of Sparse Convex Optimization is to optimize a convex function $f$ under a sparsity constraint $s\leq s^*\gamma$, where $s^*$ is the target number of non-zero entries in a feasible solution (sparsity) and $\gamma\geq 1$ is an…

Machine Learning · Computer Science 2020-06-26 Kyriakos Axiotis , Maxim Sviridenko

We present a simple deterministic distributed $(2+\epsilon)$-approximation algorithm for minimum weight vertex cover, which completes in $O(\log{\Delta}/\epsilon\log\log{\Delta})$ rounds, where $\Delta$ is the maximum degree in the graph,…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-02-15 Reuven Bar-Yehuda , Keren Censor-Hillel , Gregory Schwartzman

Consider the problem of finding a point in a unit $n$-dimensional $\ell_p$-ball ($p\ge 2$) such that the minimum of the weighted Euclidean distance from given $m$ points is maximized. We show in this paper that the recent…

Optimization and Control · Mathematics 2016-06-22 Zuping Wu , Yong Xia , Shu Wang

The Weber problem consists of finding a point in $\mathbbm{R}^n$ that minimizes the weighted sum of distances from $m$ points in $\mathbbm{R}^n$ that are not collinear. An application that motivated this problem is the optimal location of…

Optimization and Control · Mathematics 2015-03-20 Germán A. Torres

Le and Wulff-Nilsen [SODA '24] initiated a systematic study of VC set systems to unweighted $K_h$-minor-free directed graphs. We extend their results in the following ways: $\bullet$ We present the first application of VC set systems for…

Data Structures and Algorithms · Computer Science 2024-10-17 Adam Karczmarz , Da Wei Zheng

We study the problem of estimating the convex hull of the image $f(X)\subset\mathbb{R}^n$ of a compact set $X\subset\mathbb{R}^m$ with smooth boundary through a smooth function $f:\mathbb{R}^m\to\mathbb{R}^n$. Assuming that $f$ is a…

Optimization and Control · Mathematics 2024-03-11 Thomas Lew , Riccardo Bonalli , Lucas Janson , Marco Pavone

In this paper we give subexponential size hitting sets for bounded depth multilinear arithmetic formulas. Using the known relation between black-box PIT and lower bounds we obtain lower bounds for these models. For depth-3 multilinear…

Computational Complexity · Computer Science 2014-12-01 Rafael Oliveira , Amir Shpilka , Ben Lee Volk

Let X be a normed space. A subset A of X is approximately convex if $d(ta+(1-t)b,A) \le 1$ for all $a,b \in A$ and $t \in [0,1]$ where $d(x,A)$ is the distance of $x$ to $A$. Let $\Co(A)$ be the convex hull and $\diam(A)$ the diameter of…

Functional Analysis · Mathematics 2007-05-23 S. J. Dilworth , Ralph Howard , James W. Roberts

We initiate the study of approximating the largest induced expander in a given graph $G$. Given a $\Delta$-regular graph $G$ with $n$ vertices, the goal is to find the set with the largest induced expansion of size at least $\delta \cdot…

Data Structures and Algorithms · Computer Science 2015-11-10 Shayan Oveis Gharan , Alireza Rezaei

Let $\Phi = (V, \mathcal{C})$ be a constraint satisfaction problem on variables $v_1,\dots, v_n$ such that each constraint depends on at most $k$ variables and such that each variable assumes values in an alphabet of size at most $[q]$.…

Data Structures and Algorithms · Computer Science 2020-11-25 Vishesh Jain , Huy Tuan Pham , Thuy Duong Vuong

In this paper, we study two classic optimization problems: minimum geometric dominating set and set cover. In the dominating-set problem, for a given set of objects in {the} plane as input, the objective is to choose a minimum number of…

Computational Geometry · Computer Science 2022-03-22 Minati De , Abhiruk Lahiri

Given a convex set $\Omega$ of $\mathbb{R}^n$, we consider the shape optimization problem of finding a convex subset $\omega\subset \Omega$, of a given measure, minimizing the $p$-distance functional $$\mathcal{J}_p(\omega) :=…

Optimization and Control · Mathematics 2025-01-03 Zakaria Fattah , Ilias Ftouhi , Enrique Zuazua

A covering array $\mathsf{CA}(N;t,k,v)$ is an $N\times k$ array with entries in $\{1, 2, \ldots , v\}$, for which every $N\times t$ subarray contains each $t$-tuple of $\{1, 2, \ldots , v\}^t$ among its rows. Covering arrays find…

Combinatorics · Mathematics 2016-05-10 Kaushik Sarkar , Charles J. Colbourn , Annalisa De Bonis , Ugo Vaccaro

This work presents a fast and non-convex algorithm for robust subspace recovery. The data sets considered include inliers drawn around a low-dimensional subspace of a higher dimensional ambient space, and a possibly large portion of…

Machine Learning · Computer Science 2018-11-07 Gilad Lerman , Tyler Maunu
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