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The input to the NP-hard Point Line Cover problem (PLC) consists of a set $P$ of $n$ points on the plane and a positive integer $k$, and the question is whether there exists a set of at most $k$ lines which pass through all points in $P$. A…

Data Structures and Algorithms · Computer Science 2013-07-10 Stefan Kratsch , Geevarghese Philip , Saurabh Ray

We study the complexity of computing the VC Dimension and Littlestone's Dimension. Given an explicit description of a finite universe and a concept class (a binary matrix whose $(x,C)$-th entry is $1$ iff element $x$ belongs to concept…

Computational Complexity · Computer Science 2017-05-29 Pasin Manurangsi , Aviad Rubinstein

The goal of this paper is to understand how exponential-time approximation algorithms can be obtained from existing polynomial-time approximation algorithms, existing parameterized exact algorithms, and existing parameterized approximation…

Data Structures and Algorithms · Computer Science 2023-06-28 Barış Can Esmer , Ariel Kulik , Dániel Marx , Daniel Neuen , Roohani Sharma

We show that Set Cover on instances with $N$ elements cannot be approximated within $(1-\gamma)\ln N$-factor in time exp($N^{\gamma-\delta})$, for any $0 < \gamma < 1$ and any $\delta > 0$, assuming the Exponential Time Hypothesis. This…

Data Structures and Algorithms · Computer Science 2020-08-13 Marek Cygan , Magnús M. Halldórsson , Guy Kortsarz

We show improved fine-grained hardness of two key lattice problems in the $\ell_p$ norm: Bounded Distance Decoding to within an $\alpha$ factor of the minimum distance ($\mathrm{BDD}_{p, \alpha}$) and the (decisional) $\gamma$-approximate…

Computational Complexity · Computer Science 2025-07-30 Huck Bennett , Chris Peikert , Yi Tang

Permutation patterns and pattern avoidance have been intensively studied in combinatorics and computer science, going back at least to the seminal work of Knuth on stack-sorting (1968). Perhaps the most natural algorithmic question in this…

Data Structures and Algorithms · Computer Science 2019-08-14 Benjamin Aram Berendsohn , László Kozma , Dániel Marx

Counting small patterns in a large dataset is a fundamental algorithmic task. The most common version of this task is subgraph/homomorphism counting, wherein we count the number of occurrences of a small pattern graph $H$ in an input graph…

Data Structures and Algorithms · Computer Science 2025-10-21 Daniel Paul-Pena , C. Seshadhri

We establish a bound of $O(n^2k^{1+\eps})$, for any $\eps>0$, on the combinatorial complexity of the set $\T$ of line transversals of a collection $\P$ of $k$ convex polyhedra in $\reals^3$ with a total of $n$ facets, and present a…

Computational Geometry · Computer Science 2008-07-09 Haim Kaplan , Natan Rubin , Micha Sharir

We describe and analyze an algorithm for computing the homology (Betti numbers and torsion coefficients) of basic semialgebraic sets which works in weak exponential time. That is, out of a set of exponentially small measure in the space of…

Computational Geometry · Computer Science 2023-06-12 Peter Bürgisser , Felipe Cucker , Pierre Lairez

Makespan scheduling on identical machines is one of the most basic and fundamental packing problems studied in the discrete optimization literature. It asks for an assignment of $n$ jobs to a set of $m$ identical machines that minimizes the…

Data Structures and Algorithms · Computer Science 2016-04-26 Klaus Jansen , Kim-Manuel Klein , José Verschae

Cutwidth is a widely studied parameter that quantifies how well a graph can be decomposed along small edge-cuts. It complements pathwidth, which captures decomposition by small vertex separators, and it is well-known that cutwidth…

Data Structures and Algorithms · Computer Science 2025-02-25 Narek Bojikian , Vera Chekan , Stefan Kratsch

We introduce a subexponential algorithm for geometric solving of multivariate polynomial equation systems whose bit complexity depends mainly on intrinsic geometric invariants of the solution set. From this algorithm, we derive a new…

alg-geom · Mathematics 2008-02-03 M. Giusti , J. Heintz , K. Hägele , J. E. Morais , L. M. Pardo , J. L. Montaña

Tensor networks have been an important concept and technique in many research areas, such as quantum computation and machine learning. We study the exponential complexity of contracting tensor networks on two special graph structures:…

Computational Complexity · Computer Science 2023-07-06 Liu Ying

A metro-line crossing minimization problem is to draw multiple lines on an underlying graph that models stations and rail tracks so that the number of crossings of lines becomes minimum. It has several variations by adding restrictions on…

Data Structures and Algorithms · Computer Science 2013-06-18 Yoshio Okamoto , Yuichi Tatsu , Yushi Uno

Many combinatorial problems can be solved in time $O^*(c^{tw})$ on graphs of treewidth $tw$, for a problem-specific constant $c$. In several cases, matching upper and lower bounds on $c$ are known based on the Strong Exponential Time…

Computational Complexity · Computer Science 2018-06-28 Bas A. M. van Geffen , Bart M. P. Jansen , Arnoud A. W. M. de Kroon , Rolf Morel

In a recent breakthrough result, Balliu et al. [FOCS'19] proved a deterministic $\Omega(\min(\Delta,\log n /\log \log n))$-round and a randomized $\Omega(\min(\Delta,\log \log n/\log \log \log n))$-round lower bound for the complexity of…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-02-20 Sebastian Brandt , Dennis Olivetti

We study how the complexity of modular circuits computing AND depends on the depth of the circuits and the prime factorization of the modulus they use. In particular our construction of subexponential circuits of depth 2 for AND helps us to…

Computational Complexity · Computer Science 2021-06-08 Paweł M. Idziak , Piotr Kawałek , Jacek Krzaczkowski

We give nearly optimal bounds on the sample complexity of $(\widetilde{\Omega}(\epsilon),\epsilon)$-tolerant testing the $\rho$-independent set property in the dense graph setting. In particular, we give an algorithm that inspects a random…

Data Structures and Algorithms · Computer Science 2025-03-28 Cameron Seth

We introduce a new general framework for the approximation of evolution equations at low regularity and develop a new class of schemes for a wide range of equations under lower regularity assumptions than classical methods require. In…

Numerical Analysis · Mathematics 2021-02-16 Frédéric Rousset , Katharina Schratz

Stochastic interpolants offer a robust framework for continuously transforming samples between arbitrary data distributions, holding significant promise for generative modeling. Despite their potential, rigorous finite-time convergence…

Machine Learning · Computer Science 2025-08-12 Yuhao Liu , Rui Hu , Yu Chen , Longbo Huang