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We show that for all functions $t(n) \geq n$, every multitape Turing machine running in time $t$ can be simulated in space only $O(\sqrt{t \log t})$. This is a substantial improvement over Hopcroft, Paul, and Valiant's simulation of time…

Computational Complexity · Computer Science 2025-02-26 R. Ryan Williams

We consider graph Turing machines, a model of parallel computation on a graph, in which each vertex is only capable of performing one of a finite number of operations. This model of computation is a natural generalization of several…

Logic · Mathematics 2017-03-29 Nathanael Ackerman , Cameron Freer

Implementing graph algorithms efficiently in a rule-based language is challenging because graph pattern matching is expensive. In this paper, we present a number of linear-time implementations of graph algorithms in GP 2, an experimental…

Programming Languages · Computer Science 2021-01-06 Graham Campbell , Brian Courtehoute , Detlef Plump

When using graph transformation rules to implement graph algorithms, a challenge is to match the efficiency of programs in conventional languages. To help overcome that challenge, the graph programming language GP 2 features rooted rules…

Programming Languages · Computer Science 2020-12-07 Brian Courtehoute , Detlef Plump

We report on recent advances in rule-based graph programming, which allow us to match the time complexity of some fundamental imperative graph algorithms. In general, achieving the time complexity of graph algorithms implemented in…

Programming Languages · Computer Science 2026-05-27 Ziad Ismaili Alaoui , Detlef Plump

Models of computations over the integers are equivalent from a computability and complexity theory point of view by the Church-Turing thesis. It is not possible to unify discrete-time models over the reals. The situation is unclear but…

Computational Complexity · Computer Science 2024-03-06 Manon Blanc , Olivier Bournez

We describe two efficient on-line algorithms to simplify weighted graphs by eliminating degree-two vertices. Our algorithms are on-line in that they react to updates on the data, keeping the simplification up-to-date. The supported updates…

Data Structures and Algorithms · Computer Science 2007-05-23 Floris Geerts , Peter Revesz , Jan Van den Bussche

We prove that for any $\varepsilon>0$, a non-deterministic Turing machine $\mathcal{T}$ with time complexity $T(n)$ can be emulated by an $S$-machine with time and space complexities at most $T(n)^{1+\varepsilon}$ and $T(n)$, respectively.…

Group Theory · Mathematics 2023-04-18 Bogdan Chornomaz , Francis Wagner

In this paper, we show that given a weighted, directed planar graph $G$, and any $\epsilon >0$, there exists a polynomial time and $O(n^{\frac{1}{2}+\epsilon})$ space algorithm that computes the shortest path between two fixed vertices in…

Computational Complexity · Computer Science 2015-02-10 Diptarka Chakraborty , Raghunath Tewari

We propose a new (theoretical) computational model for the study of massive data processing with limited computational resources. Our model measures the complexity of reading the very large data sets in terms of the data size N and analyzes…

Data Structures and Algorithms · Computer Science 2020-03-09 Jianer Chen , Ying Guo , Qin Huang

Understanding which subclasses of quantum circuits are efficiently classically simulable is fundamental to delineating the boundary between classical and quantum computation. In this context, it is well known that certain tasks based on…

Quantum Physics · Physics 2026-03-16 Su Yeon Chang , Martin Larocca , M. Cerezo

We report on a recent breakthrough in rule-based graph programming, which allows us to reach the time complexity of imperative linear-time algorithms. In general, achieving the complexity of graph algorithms in conventional languages using…

Programming Languages · Computer Science 2025-03-27 Ziad Ismaili Alaoui , Detlef Plump

The aim of this article is to present a novel parallelization method for temporal Gaussian process (GP) regression problems. The method allows for solving GP regression problems in logarithmic O(log N) time, where N is the number of time…

Machine Learning · Computer Science 2021-05-18 Adrien Corenflos , Zheng Zhao , Simo Särkkä

For an undirected $n$-vertex graph $G$ with non-negative edge-weights, we consider the following type of query: given two vertices $s$ and $t$ in $G$, what is the weight of a minimum $st$-cut in $G$? We solve this problem in preprocessing…

Computational Geometry · Computer Science 2015-12-24 Glencora Borradaile , David Eppstein , Amir Nayyeri , Christian Wulff-Nilsen

A key task in AutoML is to model learning curves of machine learning models jointly as a function of model hyper-parameters and training progression. While Gaussian processes (GPs) are suitable for this task, na\"ive GPs require…

Machine Learning · Computer Science 2024-10-15 Jihao Andreas Lin , Sebastian Ament , Maximilian Balandat , Eytan Bakshy

Learning system dynamics directly from observations is a promising direction in machine learning due to its potential to significantly enhance our ability to understand physical systems. However, the dynamics of many real-world systems are…

Machine Learning · Computer Science 2021-03-23 Karolis Martinkus , Aurelien Lucchi , Nathanaël Perraudin

We give an algorithm to morph planar graph drawings that achieves small grid size at the expense of allowing a constant number of bends on each edge. The input is an $n$-vertex planar graph and two planar straight-line drawings of the graph…

Computational Geometry · Computer Science 2024-09-09 Therese Biedl , Anna Lubiw , Jack Spalding-Jamieson

Given a set $P$ of $n$ points in the plane and a collection of disks centered at these points, the disk graph $G(P)$ has vertex set $P$, with an edge between two vertices if their corresponding disks intersect. We study the dominating set…

Computational Geometry · Computer Science 2026-02-02 Anastasiia Tkachenko , Haitao Wang

Multi-output Gaussian processes (MOGPs) leverage the flexibility and interpretability of GPs while capturing structure across outputs, which is desirable, for example, in spatio-temporal modelling. The key problem with MOGPs is their…

Machine Learning · Statistics 2020-07-20 Wessel P. Bruinsma , Eric Perim , Will Tebbutt , J. Scott Hosking , Arno Solin , Richard E. Turner

We describe algorithms to efficiently compute minimum $(s,t)$-cuts and global minimum cuts of undirected surface-embedded graphs. Given an edge-weighted undirected graph $G$ with $n$ vertices embedded on an orientable surface of genus $g$,…

Data Structures and Algorithms · Computer Science 2019-10-11 Erin W. Chambers , Jeff Erickson , Kyle Fox , Amir Nayyeri
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