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In this paper we develop optimal algorithms in the binary-forking model for a variety of fundamental problems, including sorting, semisorting, list ranking, tree contraction, range minima, and ordered set union, intersection and difference.…

Data Structures and Algorithms · Computer Science 2020-06-26 Guy E. Blelloch , Jeremy T. Fineman , Yan Gu , Yihan Sun

We present the first polynomial-time approximation schemes, i.e., (1 + {\epsilon})-approximation algorithm for any constant {\epsilon} > 0, for the minimum three-edge connected spanning subgraph problem and the minimum three-vertex…

Data Structures and Algorithms · Computer Science 2017-01-31 Baigong Zheng

Robust estimation is much more challenging in high dimensions than it is in one dimension: Most techniques either lead to intractable optimization problems or estimators that can tolerate only a tiny fraction of errors. Recent work in…

Machine Learning · Computer Science 2018-03-14 Ilias Diakonikolas , Gautam Kamath , Daniel M. Kane , Jerry Li , Ankur Moitra , Alistair Stewart

We study a path-planning problem amid a set $\mathcal{O}$ of obstacles in $\mathbb{R}^2$, in which we wish to compute a short path between two points while also maintaining a high clearance from $\mathcal{O}$; the clearance of a point is…

Computational Geometry · Computer Science 2017-06-12 Pankaj K. Agarwal , Kyle Fox , Oren Salzman

The 3SUM problem is to decide, given a set of $n$ real numbers, whether any three sum to zero. It is widely conjectured that a trivial $O(n^2)$-time algorithm is optimal and over the years the consequences of this conjecture have been…

Data Structures and Algorithms · Computer Science 2014-06-02 Allan Grønlund , Seth Pettie

Given point sets $A$ and $B$ in $\mathbb{R}^d$ where $A$ and $B$ have equal size $n$ for some constant dimension $d$ and a parameter $\varepsilon>0$, we present the first deterministic algorithm that computes, in $n\cdot(\varepsilon^{-1}…

Data Structures and Algorithms · Computer Science 2022-04-11 Pankaj K. Agarwal , Hsien-Chih Chang , Sharath Raghvendra , Allen Xiao

Random dimensionality reduction is a versatile tool for speeding up algorithms for high-dimensional problems. We study its application to two clustering problems: the facility location problem, and the single-linkage hierarchical clustering…

Data Structures and Algorithms · Computer Science 2021-07-06 Shyam Narayanan , Sandeep Silwal , Piotr Indyk , Or Zamir

We present a dependent randomized rounding scheme, which rounds fractional solutions to integral solutions satisfying certain hard constraints on the output while preserving Chernoff-like concentration properties. In contrast to previous…

Data Structures and Algorithms · Computer Science 2025-04-29 Lars Rohwedder , Arman Rouhani , Leo Wennmann

In the online bipartite matching with reassignments problem, an algorithm is initially given only one side of the vertex set of a bipartite graph; the vertices on the other side are revealed to the algorithm one by one, along with its…

Data Structures and Algorithms · Computer Science 2020-03-12 Yongho Shin , Kangsan Kim , Seungmin Lee , Hyung-Chan An

We consider several well-studied problems in dynamic algorithms and prove that sufficient progress on any of them would imply a breakthrough on one of five major open problems in the theory of algorithms: 1. Is the 3SUM problem on $n$…

Data Structures and Algorithms · Computer Science 2014-02-04 Amir Abboud , Virginia Vassilevska Williams

The random cost problem is the problem of finding the minimum in an exponentially long list of random numbers. By definition, this problem cannot be solved faster than by exhaustive search. It is shown that a classical NP-hard optimization…

Disordered Systems and Neural Networks · Physics 2009-10-31 Stephan Mertens

This paper presents an algorithm for 3-SAT problems. First, logical formulas are transformed into elementary algebraic formulas. Second, complex trigonometric functions are assigned to the variables in the elementary algebraic formulas, and…

Data Structures and Algorithms · Computer Science 2017-08-01 Hiroshi Tsukimoto

We study the shared processor scheduling problem with a single shared processor where a unit time saving (weight) obtained by processing a job on the shared processor depends on the job. A polynomial-time optimization algorithm has been…

Discrete Mathematics · Computer Science 2021-01-19 Dariusz Dereniowski , Wieslaw Kubiak

In this paper we accomplish the development of the fast rank-adaptive solver for tensor-structured symmetric positive definite linear systems in higher dimensions. In [arXiv:1301.6068] this problem is approached by alternating minimization…

Numerical Analysis · Mathematics 2014-10-07 Sergey V. Dolgov , Dmitry V. Savostyanov

We assume the permutation $\pi$ is given by an $n$-element array in which the $i$-th element denotes the value $\pi(i)$. Constructing its inverse in-place (i.e. using $O(\log{n})$ bits of additional memory) can be achieved in linear time…

Data Structures and Algorithms · Computer Science 2020-04-22 Grzegorz Guśpiel

Optimization of three-dimensional road alignments is a nonlinear non-convex optimization problem. The development of models that fully optimize a three-dimensional road alignment problem is challenging due to numerous factors involved and…

Optimization and Control · Mathematics 2016-02-04 D. Hirpa , W. Hare , Y. Lucet , Y. Pushak , S. Tesfamariam

We study approximation algorithms for the following geometric version of the maximum coverage problem: Let P be a set of n weighted points in the plane. We want to place m a * b rectangles such that the sum of the weights of the points in P…

Computational Geometry · Computer Science 2015-05-12 Jian Li , Haitao Wang , Bowei Zhang , Ningye Zhang

We study quantum algorithms for problems in computational geometry, such as POINT-ON-3-LINES problem. In this problem, we are given a set of lines and we are asked to find a point that lies on at least $3$ of these lines. POINT-ON-3-LINES…

Computational Geometry · Computer Science 2020-04-21 Andris Ambainis , Nikita Larka

Memetic Algorithms are known to be a powerful technique in solving hard optimization problems. To design a memetic algorithm one needs to make a host of decisions; selecting a population size is one of the most important among them. Most…

Data Structures and Algorithms · Computer Science 2015-03-13 Daniel Karapetyan , Gregory Gutin

Adaptive sampling theory has shown that, with proper assumptions on the signal class, algorithms exist to reconstruct a signal in $\mathbb{R}^{d}$ with an optimal number of samples. We generalize this problem to the case of spatial signals,…

Machine Learning · Statistics 2017-02-20 John Lipor , Brandon Wong , Donald Scavia , Branko Kerkez , Laura Balzano
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