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Sparse polynomial approximation has become indispensable for approximating smooth, high- or infinite-dimensional functions from limited samples. This is a key task in computational science and engineering, e.g., surrogate modelling in…

Numerical Analysis · Mathematics 2023-11-08 Ben Adcock , Simone Brugiapaglia , Nick Dexter , Sebastian Moraga

We present a randomized algorithm for the single-source shortest paths (SSSP) problem on directed graphs with arbitrary real-valued edge weights that runs in $n^{2+o(1)}$ time with high probability. This result yields the first almost…

Data Structures and Algorithms · Computer Science 2026-02-19 Sanjeev Khanna , Junkai Song

The minimum cut problem for an undirected edge-weighted graph asks us to divide its set of nodes into two blocks while minimizing the weight sum of the cut edges. Here, we introduce a linear-time algorithm to compute near-minimum cuts. Our…

Data Structures and Algorithms · Computer Science 2019-06-05 Monika Henzinger , Alexander Noe , Christian Schulz , Darren Strash

We present fast algorithms for approximate shortest paths in the massively parallel computation (MPC) model. We provide randomized algorithms that take $poly(\log{\log{n}})$ rounds in the near-linear memory MPC model. Our results are for…

Data Structures and Algorithms · Computer Science 2025-05-20 Michal Dory , Shaked Matar

In the restricted shortest paths problem, we are given a graph $G$ whose edges are assigned two non-negative weights: lengths and delays, a source $s$, and a delay threshold $D$. The goal is to find, for each target $t$, the length of the…

Data Structures and Algorithms · Computer Science 2024-10-23 Vikrant Ashvinkumar , Aaron Bernstein , Adam Karczmarz

Center-based clustering is a fundamental primitive for data analysis and becomes very challenging for large datasets. In this paper, we focus on the popular $k$-median and $k$-means variants which, given a set $P$ of points from a metric…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-10-01 Alessio Mazzetto , Andrea Pietracaprina , Geppino Pucci

Preferential attachment lies at the heart of many network models aiming to replicate features of real world networks. To simulate the attachment process, conduct statistical tests, or obtain input data for benchmarks, efficient algorithms…

Data Structures and Algorithms · Computer Science 2023-01-18 Daniel Allendorf , Ulrich Meyer , Manuel Penschuck , Hung Tran

We present a fully dynamic algorithm for maintaining approximate maximum weight matching in general weighted graphs. The algorithm maintains a matching ${\cal M}$ whose weight is at least $1/8 M^{*}$ where $M^{*}$ is the weight of the…

Data Structures and Algorithms · Computer Science 2012-12-13 Abhash Anand , Surender Baswana , Manoj Gupta , Sandeep Sen

In this paper we present linear time approximation schemes for several generalized matching problems on nonbipartite graphs. Our results include $O_\epsilon(m)$-time algorithms for $(1-\epsilon)$-maximum weight $f$-factor and…

Data Structures and Algorithms · Computer Science 2020-05-11 Dawei Huang , Seth Pettie

We develop a framework for algorithms finding the diameter in graphs of bounded distance Vapnik-Chervonenkis dimension, in (parameterized) subquadratic time complexity. The class of bounded distance VC-dimension graphs is wide, including,…

Data Structures and Algorithms · Computer Science 2024-07-16 Lech Duraj , Filip Konieczny , Krzysztof Potępa

Graph embedding learns low-dimensional representations for nodes in a graph and effectively preserves the graph structure. Recently, a significant amount of progress has been made toward this emerging research area. However, there are…

Machine Learning · Computer Science 2019-05-20 Yuan Yin , Zhewei Wei

Expander graphs play a central role in graph theory and algorithms. With a number of powerful algorithmic tools developed around them, such as the Cut-Matching game, expander pruning, expander decomposition, and algorithms for decremental…

Data Structures and Algorithms · Computer Science 2022-12-12 Julia Chuzhoy

Distributed computing excels at processing large scale data, but the communication cost for synchronizing the shared parameters may slow down the overall performance. Fortunately, the interactions between parameter and data in many problems…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-05-19 Mu Li , Dave G. Andersen , Alexander J. Smola

We give approximation algorithms for the edge expansion and sparsest cut with product demands problems on directed hypergraphs, which subsume previous graph models such as undirected hypergraphs and directed normal graphs. Using an SDP…

Discrete Mathematics · Computer Science 2018-05-08 T-H. Hubert Chan , Bintao Sun

We introduce a new scalable approximation for Gaussian processes with provable guarantees which hold simultaneously over its entire parameter space. Our approximation is obtained from an improved sample complexity analysis for sparse…

Machine Learning · Computer Science 2020-11-18 Quang Minh Hoang , Trong Nghia Hoang , Hai Pham , David P. Woodruff

Quantum-based molecular dynamics (QMD) is a highly accurate and transferable method for material science simulations. However, the time scales and system sizes accessible to QMD are typically limited to picoseconds and a few hundred atoms.…

In undirected graphs with real non-negative weights, we give a new randomized algorithm for the single-source shortest path (SSSP) problem with running time $O(m\sqrt{\log n \cdot \log\log n})$ in the comparison-addition model. This is the…

Data Structures and Algorithms · Computer Science 2023-10-05 Ran Duan , Jiayi Mao , Xinkai Shu , Longhui Yin

We study the stable matching problem in non-bipartite graphs with incomplete but strict preference lists, where the edges have weights and the goal is to compute a stable matching of minimum or maximum weight. This problem is known to be…

Computer Science and Game Theory · Computer Science 2017-03-28 Linda Farczadi , Natália Guričanová

Suppose that we are given an arbitrary graph $G=(V, E)$ and know that each edge in $E$ is going to be realized independently with some probability $p$. The goal in the stochastic matching problem is to pick a sparse subgraph $Q$ of $G$ such…

Data Structures and Algorithms · Computer Science 2020-02-28 Soheil Behnezhad , Mahsa Derakhshan , MohammadTaghi Hajiaghayi

An instance of the Connected Maximum Cut problem consists of an undirected graph G = (V, E) and the goal is to find a subset of vertices S $\subseteq$ V that maximizes the number of edges in the cut \delta(S) such that the induced graph…

Data Structures and Algorithms · Computer Science 2015-07-03 MohammadTaghi Hajiaghayi , Guy Kortsarz , Robert MacDavid , Manish Purohit , Kanthi Sarpatwar