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In this work we review the application of the theory of Gaussian processes to the modeling of noise in pulsar-timing data analysis, and we derive various useful and optimized representations for the likelihood expressions that are needed in…

General Relativity and Quantum Cosmology · Physics 2014-11-19 Rutger van Haasteren , Michele Vallisneri

The (Non-Preemptive) Throughput Maximization problem is a natural and fundamental scheduling problem. We are given $n$ jobs, where each job $j$ is characterized by a processing time and a time window, contained in a global interval $[0,T)$,…

Data Structures and Algorithms · Computer Science 2026-04-01 Alexander Armbruster , Fabrizio Grandoni , Antoine Tinguely , Andreas Wiese

In this paper, we propose a general framework to design {efficient} polynomial time approximation schemes (EPTAS) for fundamental stochastic combinatorial optimization problems. Given an error parameter $\epsilon>0$, such algorithmic…

Data Structures and Algorithms · Computer Science 2025-05-30 Danny Segev , Sahil Singla

We give the first polynomial-time approximation scheme (PTAS) for the Steiner forest problem on planar graphs and, more generally, on graphs of bounded genus. As a first step, we show how to build a Steiner forest spanner for such graphs.…

Data Structures and Algorithms · Computer Science 2009-11-30 MohammadHossein Bateni , MohammadTaghi Hajiaghayi , Dániel Marx

We study approximability of subdense instances of various covering problems on graphs, defined as instances in which the minimum or average degree is Omega(n/psi(n)) for some function psi(n)=omega(1) of the instance size. We design new…

Data Structures and Algorithms · Computer Science 2010-11-10 Jean Cardinal , Marek Karpinski , Richard Schmied , Claus Viehmann

We study the problem of approximating the value of the matching polynomial on graphs with edge parameter $\gamma$, where $\gamma$ takes arbitrary values in the complex plane. When $\gamma$ is a positive real, Jerrum and Sinclair showed that…

Discrete Mathematics · Computer Science 2021-01-13 Ivona Bezakova , Andreas Galanis , Leslie Ann Goldberg , Daniel Stefankovic

In this paper, we will find a pseudopolynomial algorithm to solve $Qm \mid \mid L_{\max}$ and then we will prove that it is impossible to get any constant-factor approximation in polynomial time, and thus also impossible to have a PTAS for…

Data Structures and Algorithms · Computer Science 2020-01-23 Elbert Du , Stan Zhang

We study the classical scheduling problem of minimizing the makespan of a set of unit size jobs with precedence constraints on parallel identical machines. Research on the problem dates back to the landmark paper by Graham from 1966 who…

Data Structures and Algorithms · Computer Science 2025-01-17 Syamantak Das , Andreas Wiese

We consider the classic Facility Location problem on planar graphs (non-uniform, uncapacitated). Given an edge-weighted planar graph $G$, a set of clients $C\subseteq V(G)$, a set of facilities $F\subseteq V(G)$, and opening costs…

Data Structures and Algorithms · Computer Science 2019-04-25 Vincent Cohen-Addad , Marcin Pilipczuk , Michał Pilipczuk

Many functions have approximately-known upper and/or lower bounds, potentially aiding the modeling of such functions. In this paper, we introduce Gaussian process models for functions where such bounds are (approximately) known. More…

Machine Learning · Computer Science 2022-10-20 Vu Nguyen , Marc Peter Deisenroth , Michael A. Osborne

The seminal papers of Pickands [1,2] paved the way for a systematic study of high exceedance probabilities of both stationary and non-stationary Gaussian processes. Yet, in the vector-valued setting, due to the lack of key tools including…

Probability · Mathematics 2019-11-18 Krzysztof Dȩbicki , Enkelejd Hashorva , Longmin Wang

In this paper we develop non-asymptotic Gaussian approximation results for the sampling distribution of suprema of empirical processes when the indexing function class $\mathcal{F}_n$ varies with the sample size $n$ and may not be Donsker.…

Statistics Theory · Mathematics 2023-09-06 Alexander Giessing

We study the general scheduling problem (GSP) which generalizes and unifies several well-studied preemptive single-machine scheduling problems, such as weighted flow time, weighted sum of completion time, and minimizing the total weight of…

Data Structures and Algorithms · Computer Science 2025-11-21 Alexander Armbruster , Lars Rohwedder , Andreas Wiese

We exhibit a strong connection between cover times of graphs, Gaussian processes, and Talagrand's theory of majorizing measures. In particular, we show that the cover time of any graph $G$ is equivalent, up to universal constants, to the…

Probability · Mathematics 2011-10-10 Jian Ding , James R. Lee , Yuval Peres

The interval subset sum problem (ISSP) is a generalization of the well-known subset sum problem. Given a set of intervals $\left\{[a_{i,1},a_{i,2}]\right\}_{i=1}^n$ and a target integer $T,$ the ISSP is to find a set of integers, at most…

Data Structures and Algorithms · Computer Science 2017-04-25 Rui Diao , Ya-Feng Liu , Yu-Hong Dai

Positive semidefinite programs are an important subclass of semidefinite programs in which all matrices involved in the specification of the problem are positive semidefinite and all scalars involved are non-negative. We present a parallel…

Computational Complexity · Computer Science 2011-04-14 Rahul Jain , Penghui Yao

This paper is about the length $X_{\rm MAX}$ of the longest path in directed acyclic graph (DAG) $G=(V,E)$ with random edge lengths, where $|V|=n$ and $|E|=m$. When the edge lengths are mutually independent and uniformly distributed, the…

Computational Complexity · Computer Science 2022-03-29 Ei Ando

We consider a recently introduced fair repetitive scheduling problem involving a set of clients, each asking for their associated job to be daily scheduled on a single machine across a finite planning horizon. The goal is to determine a job…

Data Structures and Algorithms · Computer Science 2026-01-01 Danny Hermelin , Danny Segev , Dvir Shabtay

Gaussian processes (GPs) are flexible, probabilistic, nonparametric models widely used in fields such as spatial statistics and machine learning. A drawback of Gaussian processes is their computational cost, with $O(N^3)$ time and $O(N^2)$…

Computation · Statistics 2026-05-20 Filippo Rambelli , Fabio Sigrist

We show the existence of a fully polynomial-time approximation scheme (FPTAS) for the problem of maximizing a non-negative polynomial over mixed-integer sets in convex polytopes, when the number of variables is fixed. Moreover, using a…

Optimization and Control · Mathematics 2017-01-03 Jesús A. De Loera , Raymond Hemmecke , Matthias Köppe , Robert Weismantel