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Greedy algorithms are widely used for problems in machine learning such as feature selection and set function optimization. Unfortunately, for large datasets, the running time of even greedy algorithms can be quite high. This is because for…

Machine Learning · Statistics 2017-03-09 Rajiv Khanna , Ethan Elenberg , Alexandros G. Dimakis , Sahand Negahban , Joydeep Ghosh

In this paper we study graph problems in dynamic streaming model, where the input is defined by a sequence of edge insertions and deletions. As many natural problems require $\Omega(n)$ space, where $n$ is the number of vertices, existing…

Data Structures and Algorithms · Computer Science 2016-05-03 Zengfeng Huang , Pan Peng

Sampling edges from a graph in sublinear time is a fundamental problem and a powerful subroutine for designing sublinear-time algorithms. Suppose we have access to the vertices of the graph and know a constant-factor approximation to the…

Data Structures and Algorithms · Computer Science 2022-11-15 Talya Eden , Shyam Narayanan , Jakub Tětek

We investigate sublinear-time algorithms that take partially erased graphs represented by adjacency lists as input. Our algorithms make degree and neighbor queries to the input graph and work with a specified fraction of adversarial…

Data Structures and Algorithms · Computer Science 2020-12-01 Amit Levi , Ramesh Krishnan S. Pallavoor , Sofya Raskhodnikova , Nithin Varma

Probabilistic graphical models offer a powerful framework to account for the dependence structure between variables, which is represented as a graph. However, the dependence between variables may render inference tasks intractable. In this…

We study space-pass tradeoffs in graph streaming algorithms for parameter estimation and property testing problems such as estimating the size of maximum matchings and maximum cuts, weight of minimum spanning trees, or testing if a graph is…

Data Structures and Algorithms · Computer Science 2021-04-13 Sepehr Assadi , Vishvajeet N

We study the complexity of local graph centrality estimation, with the goal of approximating the centrality score of a given target node while exploring only a sublinear number of nodes/arcs of the graph and performing a sublinear number of…

Data Structures and Algorithms · Computer Science 2018-08-07 Marco Bressan , Enoch Peserico , Luca Pretto

In this paper we propose and study a new complexity model for approximation algorithms. The main motivation are practical problems over large data sets that need to be solved many times for different scenarios, e.g., many multicast trees…

Data Structures and Algorithms · Computer Science 2010-06-18 Marek Cygan , Lukasz Kowalik , Marcin Mucha , Marcin Pilipczuk , Piotr Sankowski

Many streaming algorithms provide only a high-probability relative approximation. These two relaxations, of allowing approximation and randomization, seem necessary -- for many streaming problems, both relaxations must be employed…

Data Structures and Algorithms · Computer Science 2023-05-16 Vladimir Braverman , Robert Krauthgamer , Aditya Krishnan , Shay Sapir

Calculating the diameter of an undirected graph requires quadratic running time under the Strong Exponential Time Hypothesis and this barrier works even against any approximation better than 3/2. For planar graphs with positive edge…

Data Structures and Algorithms · Computer Science 2025-07-08 Michał Włodarczyk

In the classic online graph balancing problem, edges arrive sequentially and must be oriented immediately upon arrival, to minimize the maximum in-degree. For adversarial arrivals, the natural greedy algorithm is $O(\log n)$-competitive,…

Data Structures and Algorithms · Computer Science 2026-04-07 Nikhil Bansal , Milind Prabhu , Sahil Singla , Siddharth M. Sundaram

Distributed algorithms are often beset by the straggler effect, where the slowest compute nodes in the system dictate the overall running time. Coding-theoretic techniques have been recently proposed to mitigate stragglers via algorithmic…

Machine Learning · Statistics 2017-11-21 Zachary Charles , Dimitris Papailiopoulos , Jordan Ellenberg

We consider the minimum cut problem in undirected, weighted graphs. We give a simple algorithm to find a minimum cut that $2$-respects (cuts two edges of) a spanning tree $T$ of a graph $G$. This procedure can be used in place of the…

Data Structures and Algorithms · Computer Science 2020-06-11 Nalin Bhardwaj , Antonio Molina Lovett , Bryce Sandlund

Weighted variants of triangle detection are an important object of study because of their prominence in fine-grained complexity. We revisit the Node-Weighted Triangle problem, where the goal is to decide if a vertex-weighted graph contains…

Data Structures and Algorithms · Computer Science 2026-05-12 Shyan Akmal , Nick Fischer

Given $n$ points in the plane, we propose algorithms to compile connected crossing-free geometric graphs into directed acyclic graphs (DAGs). The DAGs allow efficient counting, enumeration, random sampling, and optimization. Our algorithms…

Computational Geometry · Computer Science 2020-01-27 Yu Nakahata , Takashi Horiyama , Shin-ichi Minato , Katsuhisa Yamanaka

We study the problem of coloring a given graph using a small number of colors in several well-established models of computation for big data. These include the data streaming model, the general graph query model, the massively parallel…

Data Structures and Algorithms · Computer Science 2019-05-03 Suman K. Bera , Amit Chakrabarti , Prantar Ghosh

Given a $k$-node pattern graph $H$ and an $n$-node host graph $G$, the subgraph counting problem asks to compute the number of copies of $H$ in $G$. In this work we address the following question: can we count the copies of $H$ faster if…

Computational Complexity · Computer Science 2020-09-01 Marco Bressan

Let G=(V,E) be a graph with f:V\to Z_+ a function assigning degree bounds to vertices. We present the first efficient algebraic algorithm to find an f-factor. The time is \tilde{O}(f(V)^{\omega}). More generally for graphs with integral…

Data Structures and Algorithms · Computer Science 2013-04-26 Harold N. Gabow , Piotr Sankowski

We present an implementation and an experimental evaluation of an algorithm that, given a connected graph G (represented by adjacency lists), estimates in sublinear time, with a relative error, the Minimum Spanning Tree Weight of G; the…

Data Structures and Algorithms · Computer Science 2017-01-30 Gabriele Santi , Leonardo De Laurentiis

Let $G$ be an $n$-vertex graph with $m$ edges. When asked a subset $S$ of vertices, a cut query on $G$ returns the number of edges of $G$ that have exactly one endpoint in $S$. We show that there is a bounded-error quantum algorithm that…

Data Structures and Algorithms · Computer Science 2020-08-05 Troy Lee , Miklos Santha , Shengyu Zhang