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This thesis explores algorithmic applications and limitations of convex relaxation hierarchies for approximating some discrete and continuous optimization problems. - We show a dichotomy of approximability of constraint satisfaction…

Computational Complexity · Computer Science 2025-09-01 Mrinalkanti Ghosh

A fundamental problem in shape matching and geometric similarity is computing the maximum area overlap between two polygons under translation. For general simple polygons, the best-known algorithm runs in $O((nm)^2 \log(nm))$ time [Mount,…

Computational Geometry · Computer Science 2025-11-07 Mikkel Abrahamsen , Sujoy Bhore , Maike Buchin , Jacobus Conradi , Ce Jin , André Nusser , Carolin Rehs

Bereg et al. (2012) introduced the Boxes Class Cover problem, which has its roots in classification and clustering applications: Given a set of n points in the plane, each colored red or blue, find the smallest cardinality set of…

Computational Geometry · Computer Science 2021-06-25 Jean Cardinal , Justin Dallant , John Iacono

We study the problem of optimizing assortment decisions in the presence of product-specific costs when customers choose according to a multinomial logit model. This problem is NP-hard and approximate solutions methods have been proposed in…

Optimization and Control · Mathematics 2023-12-05 Markus Leitner , Andrea Lodi , Roberto Roberti , Claudio Sole

In the snippets problem, the goal is to preprocess text $T$ so that given two patterns $P_1$ and $P_2$, one can locate the occurrences of the two patterns in $T$ that are closest to each other, or report their distance. Kopelowitz and…

Data Structures and Algorithms · Computer Science 2025-07-08 Noam Horowicz , Tsvi Kopelowitz

This paper is devoted to the theoretical and numerical investigation of an augmented Lagrangian method for the solution of optimization problems with geometric constraints. Specifically, we study situations where parts of the constraints…

Optimization and Control · Mathematics 2022-04-20 Xiaoxi Jia , Christian Kanzow , Patrick Mehlitz , Gerd Wachsmuth

In this paper, we give a faster width-dependent algorithm for mixed packing-covering LPs. Mixed packing-covering LPs are fundamental to combinatorial optimization in computer science and operations research. Our algorithm finds a $1+\eps$…

Optimization and Control · Mathematics 2019-10-15 Digvijay Boob , Saurabh Sawlani , Di Wang

We give an $\alpha(1+\epsilon)$-approximation algorithm for solving covering LPs, assuming the presence of a $(1/\alpha)$-approximation algorithm for a certain optimization problem. Our algorithm is based on a simple modification of the…

Data Structures and Algorithms · Computer Science 2020-12-18 Eklavya Sharma

We present a nearly linear work parallel algorithm for approximating the Held-Karp bound for the Metric TSP problem. Given an edge-weighted undirected graph $G=(V,E)$ on $m$ edges and $\epsilon>0$, it returns a $(1+\epsilon)$-approximation…

Data Structures and Algorithms · Computer Science 2025-06-24 Zhuan Khye Koh , Omri Weinstein , Sorrachai Yingchareonthawornchai

We study computational aspects of a key problem in robust statistics -- the penalized least trimmed squares (LTS) regression problem, a robust estimator that mitigates the influence of outliers in data by capping residuals with large…

Optimization and Control · Mathematics 2026-04-15 Xiang Meng , Andrés Gómez , Rahul Mazumder

We give a proof of the conjecture of Nelson and Nguyen [FOCS 2013] on the optimal dimension and sparsity of oblivious subspace embeddings, up to sub-polylogarithmic factors: For any $n\geq d$ and $\epsilon\geq d^{-O(1)}$, there is a random…

Data Structures and Algorithms · Computer Science 2025-11-18 Shabarish Chenakkod , Michał Dereziński , Xiaoyu Dong

In many applications, we need algorithms which can align partially overlapping point sets and are invariant to the corresponding transformations. In this work, a method possessing such properties is realized by minimizing the objective of…

Computer Vision and Pattern Recognition · Computer Science 2023-07-06 Wei Lian , Wangmeng Zuo

A solution manifold is the collection of points in a $d$-dimensional space satisfying a system of $s$ equations with $s<d$. Solution manifolds occur in several statistical problems including hypothesis testing, curved-exponential families,…

Statistics Theory · Mathematics 2021-12-15 Yen-Chi Chen

The min-knapsack problem with compactness constraints extends the classical knapsack problem, in the case of ordered items, by introducing a restriction ensuring that they cannot be too far apart. This problem has applications in…

Optimization and Control · Mathematics 2025-04-28 Hubert Villuendas , Mathieu Besançon , Jérôme Malick

In this work, we study the classic submodular maximization problem under knapsack constraints and beyond. We first present an $(7/16-\varepsilon)$-approximate algorithm for single knapsack constraint, which requires…

Data Structures and Algorithms · Computer Science 2020-12-22 Wenxin Li

The chosen tool of this thesis is an extremal type approach. The lesson drawn by the theorems proved in the thesis is that surprisingly small compromise is necessary on the efficacy of the solutions to make the approach work. The problems…

Combinatorics · Mathematics 2017-11-09 Tamás Róbert Mezei

Thepaperprovesconvergenceofone-levelandmultilevelunsymmetriccollocationforsecondorderelliptic boundary value problems on the bounded domains. By using Schaback's linear discretization theory,L2 errors are obtained based on the kernel-based…

Numerical Analysis · Mathematics 2023-06-16 Zhiyong Liu , Qiuyan Xu

The Tammes problem delves into the optimal arrangement of $N$ points on the surface of the $n$-dimensional unit sphere (denoted as $\mathbb{S}^{n-1}$), aiming to maximize the minimum distance between any two points. In this paper, we…

Metric Geometry · Mathematics 2024-11-26 Yanlu Lian , Qun Mo , Yu Xia

We show how to solve a number of problems in numerical linear algebra, such as least squares regression, $\ell_p$-regression for any $p \geq 1$, low rank approximation, and kernel regression, in time $T(A) \poly(\log(nd))$, where for a…

Machine Learning · Computer Science 2019-12-13 Xiaofei Shi , David P. Woodruff

We consider distributed stochastic optimization problems that are solved with master/workers computation architecture. Statistical arguments allow to exploit statistical similarity and approximate this problem by a finite-sum problem, for…