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The problem of identifying a planted assignment given a random $k$-SAT formula consistent with the assignment exhibits a large algorithmic gap: while the planted solution becomes unique and can be identified given a formula with $O(n\log…

Computational Complexity · Computer Science 2018-03-07 Vitaly Feldman , Will Perkins , Santosh Vempala

Spike sorting is a class of algorithms used in neuroscience to attribute the time occurences of particular electric signals, called action potential or spike, to neurons. We rephrase this problem as a particular optimization problem : Lasso…

Statistics Theory · Mathematics 2022-04-12 Laurent Dragoni , Rémi Flamary , Karim Lounici , Patricia Reynaud-Bouret

Pattern matching is a fundamental process in almost every scientific domain. The problem involves finding the positions of a given pattern (usually of short length) in a reference stream of data (usually of large length). The matching can…

Data Structures and Algorithms · Computer Science 2022-07-01 Anas Al-okaily , Abdelghani Tbakhi

Given $k$ collections of 2SAT clauses on the same set of variables $V$, can we find one assignment that satisfies a large fraction of clauses from each collection? We consider such simultaneous constraint satisfaction problems, and design…

Data Structures and Algorithms · Computer Science 2014-07-30 Amey Bhangale , Swastik Kopparty , Sushant Sachdeva

An influential result by Dor, Halperin, and Zwick (FOCS 1996, SICOMP 2000) implies an algorithm that can compute approximate shortest paths for all vertex pairs in $\tilde{O}(n^{2+O\left(\frac{1}{k}\right )})$ time, ensuring that the output…

Data Structures and Algorithms · Computer Science 2025-07-29 Manoj Gupta

In the discrete $k$-center problem, we are given a metric space $(P,\texttt{dist})$ where $|P|=n$ and the goal is to select a set $C\subseteq P$ of $k$ centers which minimizes the maximum distance of a point in $P$ from its nearest center.…

Computational Geometry · Computer Science 2022-03-17 Rajesh Chitnis , Nitin Saurabh

Let ${\cal G}$ be a minor-closed graph class and let $G$ be an $n$-vertex graph. We say that $G$ is a $k$-apex of ${\cal G}$ if $G$ contains a set $S$ of at most $k$ vertices such that $G\setminus S$ belongs to ${\cal G}$. Our first result…

Data Structures and Algorithms · Computer Science 2024-08-14 Laure Morelle , Ignasi Sau , Giannos Stamoulis , Dimitrios M. Thilikos

Confidence intervals are a standard technique for analyzing data. When applied to time series, confidence intervals are computed for each time point separately. Alternatively, we can compute confidence bands, where we are required to find…

Machine Learning · Computer Science 2021-12-14 Nikolaj Tatti

The sum of radii problem ($k$-MSR) asks, given a metric space on $n$ points, to place $k$ balls covering all points so as to minimize the sum of their radii. Despite extensive study from the perspectives of approximation and parameterized…

Data Structures and Algorithms · Computer Science 2026-05-08 Ameet Gadekar

We consider the stochastic $k$-TSP problem where rewards at vertices are random and the objective is to minimize the expected length of a tour that collects reward $k$. We present an adaptive $O(\log k)$-approximation algorithm, and a…

Data Structures and Algorithms · Computer Science 2016-10-05 Alina Ene , Viswanath Nagarajan , Rishi Saket

One of the most fundamental problems in Computer Science is the Knapsack problem. Given a set of n items with different weights and values, it asks to pick the most valuable subset whose total weight is below a capacity threshold T. Despite…

Data Structures and Algorithms · Computer Science 2018-07-16 Kyriakos Axiotis , Christos Tzamos

We study the classic NP-Hard problem of finding the maximum $k$-set coverage in the data stream model: given a set system of $m$ sets that are subsets of a universe $\{1,\ldots,n \}$, find the $k$ sets that cover the most number of distinct…

Data Structures and Algorithms · Computer Science 2018-05-11 Andrew McGregor , Hoa T. Vu

Let $A$ and $B$ be two point sets in the plane of sizes $r$ and $n$ respectively (assume $r \leq n$), and let $k$ be a parameter. A matching between $A$ and $B$ is a family of pairs in $A \times B$ so that any point of $A \cup B$ appears in…

Data Structures and Algorithms · Computer Science 2019-03-25 Pankaj K. Agarwal , Hsien-Chih Chang , Allen Xiao

We study the problem of metrical service systems with multiple servers (MSSMS), which generalizes two well-known problems -- the $k$-server problem, and metrical service systems. The MSSMS problem is to service requests, each of which is an…

Data Structures and Algorithms · Computer Science 2014-05-22 Ashish Chiplunkar , Sundar Vishwanathan

Lattices are very important objects in the effort to construct cryptographic primitives that are secure against quantum attacks. A central problem in the study of lattices is that of finding the shortest non-zero vector in the lattice.…

Quantum Physics · Physics 2022-09-05 Nishant Rodrigues , Brad Lackey

We introduce here a rewrite system in the group of unimodular matrices, \emph{i.e.}, matrices with integer entries and with determinant equal to $\pm 1$. We use this rewrite system to precisely characterize the mechanism of the Gaussian…

Data Structures and Algorithms · Computer Science 2007-07-05 Ali Akhavi , Céline Moreira

We prove that some exact geometric pattern matching problems reduce in linear time to $k$-SUM when the pattern has a fixed size $k$. This holds in the real RAM model for searching for a similar copy of a set of $k\geq 3$ points within a set…

Computational Geometry · Computer Science 2020-03-27 Boris Aronov , Jean Cardinal

The lower and the upper irredundance numbers of a graph $G$, denoted $ir(G)$ and $IR(G)$ respectively, are conceptually linked to domination and independence numbers and have numerous relations to other graph parameters. It is a…

In this work, we propose an optimization framework for estimating a sparse robust one-dimensional subspace. Our objective is to minimize both the representation error and the penalty, in terms of the l1-norm criterion. Given that the…

Machine Learning · Statistics 2024-03-07 Xiao Ling , Paul Brooks

We introduce a novel scheme for choosing the regularization parameter in high-dimensional linear regression with Lasso. This scheme, inspired by Lepski's method for bandwidth selection in non-parametric regression, is equipped with both…

Methodology · Statistics 2016-11-09 Michaël Chichignoud , Johannes Lederer , Martin Wainwright