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Given a redundant dictionary $\Phi$, represented by an $M \times N$ matrix ($\Phi \in \mathbb{R}^{M \times N}$) and a target signal $y \in \mathbb{R}^M$, the \emph{sparse approximation problem} asks to find an approximate representation of…

Computational Complexity · Computer Science 2011-11-29 Ali Civril

The level set estimation problem seeks to find all points in a domain ${\cal X}$ where the value of an unknown function $f:{\cal X}\rightarrow \mathbb{R}$ exceeds a threshold $\alpha$. The estimation is based on noisy function evaluations…

Machine Learning · Statistics 2021-11-03 Blake Mason , Romain Camilleri , Subhojyoti Mukherjee , Kevin Jamieson , Robert Nowak , Lalit Jain

We design an algorithm for approximating the size of \emph{Max Cut} in dense graphs. Given a proximity parameter $\varepsilon \in (0,1)$, our algorithm approximates the size of \emph{Max Cut} of a graph $G$ with $n$ vertices, within an…

Data Structures and Algorithms · Computer Science 2021-12-21 Arijit Ghosh , Gopinath Mishra , Rahul Raychaudhury , Sayantan Sen

Maximum bipartite matching is a fundamental algorithmic problem which can be solved in polynomial time. We consider a natural variant in which there is a separation constraint: the vertices on one side lie on a path or a grid, and two…

Data Structures and Algorithms · Computer Science 2023-03-20 Pasin Manurangsi , Erel Segal-Halevi , Warut Suksompong

An $\epsilon$-approximate incidence between a point and some geometric object (line, circle, plane, sphere) occurs when the point and the object lie at distance at most $\epsilon$ from each other. Given a set of points and a set of objects,…

Computational Geometry · Computer Science 2020-05-19 Dror Aiger , Haim Kaplan , Micha Sharir

The concept of data depth in non-parametric multivariate descriptive statistics is the generalization of the univariate rank method to multivariate data. Halfspace depth is a measure of data depth. Given a set S of points and a point p, the…

Computational Geometry · Computer Science 2007-05-23 Dan Chen

We show improved NP-hardness of approximating Ordering Constraint Satisfaction Problems (OCSPs). For the two most well-studied OCSPs, Maximum Acyclic Subgraph and Maximum Betweenness, we prove inapproximability of $14/15+\epsilon$ and…

Computational Complexity · Computer Science 2013-07-22 Per Austrin , Rajsekar Manokaran , Cenny Wenner

A common way to quantify the ,,distance'' between measures is via their discrepancy, also known as maximum mean discrepancy (MMD). Discrepancies are related to Sinkhorn divergences $S_\varepsilon$ with appropriate cost functions as…

Optimization and Control · Mathematics 2020-08-25 Sebastian Neumayer , Gabriele Steidl

We consider the discrepancy problem of coloring $n$ intervals with $k$ colors such that at each point on the line, the maximal difference between the number of intervals of any two colors is minimal. Somewhat surprisingly, a coloring with…

Data Structures and Algorithms · Computer Science 2010-12-20 Antonios Antoniadis , Falk Hüffner , Pascal Lenzner , Carsten Moldenhauer , Alexander Souza

We consider the family of $\Phi$-Subset problems, where the input consists of an instance $I$ of size $N$ over a universe $U_I$ of size $n$ and the task is to check whether the universe contains a subset with property $\Phi$ (e.g., $\Phi$…

Data Structures and Algorithms · Computer Science 2017-04-27 Serge Gaspers , Edward Lee

Bias evaluation is fundamental to trustworthy AI, both in terms of checking data quality and in terms of checking the outputs of AI systems. In testing data quality, for example, one may study the distance of a given dataset, viewed as a…

Machine Learning · Computer Science 2025-06-12 Jiří Němeček , Mark Kozdoba , Illia Kryvoviaz , Tomáš Pevný , Jakub Mareček

Given a source of iid samples of edges of an input graph $G$ with $n$ vertices and $m$ edges, how many samples does one need to compute a constant factor approximation to the maximum matching size in $G$? Moreover, is it possible to obtain…

Data Structures and Algorithms · Computer Science 2019-07-15 Michael Kapralov , Slobodan Mitrović , Ashkan Norouzi-Fard , Jakab Tardos

The expansion of a hypergraph, a natural extension of the notion of expansion in graphs, is defined as the minimum over all cuts in the hypergraph of the ratio of the number of the hyperedges cut to the size of the smaller side of the cut.…

Data Structures and Algorithms · Computer Science 2014-04-18 Anand Louis , Yury Makarychev

In the hypothesis selection problem, we are given sample and query access to finite set of candidate distributions (hypotheses), $\mathcal{H} = \{H_1, \ldots, H_n\}$, and samples from an unknown distribution $P$, both over a domain…

Data Structures and Algorithms · Computer Science 2025-11-12 Anders Aamand , Maryam Aliakbarpour , Justin Y. Chen , Sandeep Silwal

This paper studies the properties of a new lower bound for the natural pseudo-distance. The natural pseudo-distance is a dissimilarity measure between shapes, where a shape is viewed as a topological space endowed with a real-valued…

Computational Geometry · Computer Science 2008-04-23 M. d'Amico , P. Frosini , C. Landi

A family $\mathcal{R}$ of ranges and a set $X$ of points together define a range space $(X, \mathcal{R}|_X)$, where $\mathcal{R}|_X = \{X \cap h \mid h \in \mathcal{R}\}$. We want to find a structure to estimate the quantity $|X \cap…

Computational Geometry · Computer Science 2019-03-18 Yufei Tao , Yu Wang

The approximation of a general $d$-variate function $f$ by the shifts $\phi(\cdot-\xi)$, $\xi\in\Xi\subset \Rd$, of a fixed function $\phi$ occurs in many applications such as data fitting, neural networks, and learning theory. When…

Classical Analysis and ODEs · Mathematics 2008-02-19 Ronald DeVore , Amos Ron

In the problem of semialgebraic range searching, we are to preprocess a set of points in $\mathbb{R}^D$ such that the subset of points inside a semialgebraic region described by $O(1)$ polynomial inequalities of degree $\Delta$ can be found…

Computational Geometry · Computer Science 2022-03-16 Peyman Afshani , Pingan Cheng

An NP-hard combinatorial optimization problem $\Pi$ is said to have an {\em approximation threshold} if there is some $t$ such that the optimal value of $\Pi$ can be approximated in polynomial time within a ratio of $t$, and it is NP-hard…

Computational Complexity · Computer Science 2008-12-15 Uriel Feige

In this article we consider the graph alignment problem from the perspective of high-dimensional statistics: we aim to estimate an unknown permutation $\pi^*$ from the observation of two correlated random adjacency matrices $A_1$, $A_2$. We…

Probability · Mathematics 2025-10-30 Laurent Massoulié
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