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For a set $P$ of $n$ points in the plane and a value $r > 0$, the unit-disk range reporting problem is to construct a data structure so that given any query disk of radius $r$, all points of $P$ in the disk can be reported efficiently. We…

Computational Geometry · Computer Science 2025-01-03 Haitao Wang , Yiming Zhao

A Random Access query to a string $T\in [0..\sigma)^n$ asks for the character $T[i]$ at a given position $i\in [0..n)$. In $O(n\log\sigma)$ bits of space, this fundamental task admits constant-time queries. While this is optimal in the…

Data Structures and Algorithms · Computer Science 2026-05-13 Anouk Duyster , Tomasz Kociumaka

In this paper we study lower bounds for the fundamental problem of text indexing with mismatches and differences. In this problem we are given a long string of length $n$, the "text", and the task is to preprocess it into a data structure…

Data Structures and Algorithms · Computer Science 2018-12-24 Vincent Cohen-Addad , Laurent Feuilloley , Tatiana Starikovskaya

In a dynamic retrieval system, documents must be ingested as they arrive, and be immediately findable by queries. Our purpose in this paper is to describe an index structure and processing regime that accommodates that requirement for…

Information Retrieval · Computer Science 2023-01-12 Alistair Moffat , Joel Mackenzie

Navarro and Sadakane [TALG 2014] gave a dynamic succinct data structure for storing an ordinal tree. The structure supports tree queries in either $O(\log n/\log\log n)$ or $O(\log n)$ time, and insertion or deletion of a single node in…

Data Structures and Algorithms · Computer Science 2018-05-30 Dekel Tsur

In this paper we show that two-dimensional nearest neighbor queries can be answered in optimal $O(\log n)$ time while supporting insertions in $O(\log^{1+\varepsilon}n)$ time. No previous data structure was known that supports $O(\log…

Data Structures and Algorithms · Computer Science 2025-04-11 John Iacono , Yakov Nekrich

Sliding-window aggregation is a widely-used approach for extracting insights from the most recent portion of a data stream. The aggregations of interest can usually be expressed as binary operators that are associative but not necessarily…

Databases · Computer Science 2020-09-30 Kanat Tangwongsan , Martin Hirzel , Scott Schneider

Given a planar map of $n$ segments in which we wish to efficiently locate points, we present the first randomized incremental construction of the well-known trapezoidal-map search-structure that only requires expected $O(n \log n)$…

Computational Geometry · Computer Science 2014-10-22 Michael Hemmer , Michal Kleinbort , Dan Halperin

We revisit classic string problems considered in the area of parameterized complexity, and study them through the lens of dynamic data structures. That is, instead of asking for a static algorithm that solves the given instance efficiently,…

Data Structures and Algorithms · Computer Science 2022-05-03 Jędrzej Olkowski , Michał Pilipczuk , Mateusz Rychlicki , Karol Węgrzycki , Anna Zych-Pawlewicz

We consider the problem of testing graph cluster structure: given access to a graph $G=(V, E)$, can we quickly determine whether the graph can be partitioned into a few clusters with good inner conductance, or is far from any such graph?…

Data Structures and Algorithms · Computer Science 2018-09-19 Ashish Chiplunkar , Michael Kapralov , Sanjeev Khanna , Aida Mousavifar , Yuval Peres

In edge orientations, the goal is usually to orient (direct) the edges of an undirected $n$-vertex graph $G$ such that all out-degrees are bounded. When the graph $G$ is fully dynamic, i.e., admits edge insertions and deletions, we wish to…

Data Structures and Algorithms · Computer Science 2013-12-06 Tsvi Kopelowitz , Robert Krauthgamer , Ely Porat , Shay Solomon

In the range $\alpha$-majority query problem, we are given a sequence $S[1..n]$ and a fixed threshold $\alpha \in (0, 1)$, and are asked to preprocess $S$ such that, given a query range $[i..j]$, we can efficiently report the symbols that…

Data Structures and Algorithms · Computer Science 2018-05-24 Travis Gagie , Meng He , Gonzalo Navarro

Differential computation (DC) is a highly general incremental computation/view maintenance technique that can maintain the output of an arbitrary and possibly recursive dataflow computation upon changes to its base inputs. As such, it is a…

Databases · Computer Science 2022-08-02 Khaled Ammar , Siddhartha Sahu , Semih Salihoglu , M. Tamer Ozsu

This paper shows the weighted matching problem on general graphs can be solved in time $O(n(m + n\log n))$ for $n$ and $m$ the number of vertices and edges, respectively. This was previously known only for bipartite graphs. The crux is a…

Data Structures and Algorithms · Computer Science 2016-11-24 Harold N. Gabow

We consider compact representations of collections of similar strings that support random access queries. The collection of strings is given by a rooted tree where edges are labeled by an edit operation (inserting, deleting, or replacing a…

Data Structures and Algorithms · Computer Science 2021-02-12 Philip Bille , Inge Li Gørtz

We revisit the classic problem of simplex range searching and related problems in computational geometry. We present a collection of new results which improve previous bounds by multiple logarithmic factors that were caused by the use of…

Computational Geometry · Computer Science 2022-10-24 Timothy M. Chan , Da Wei Zheng

In this paper, we consider two fundamental cut approximation problems on large graphs. We prove new lower bounds for both problems that are optimal up to logarithmic factors. The first problem is to approximate cuts in balanced directed…

Data Structures and Algorithms · Computer Science 2024-06-21 Yu Cheng , Max Li , Honghao Lin , Zi-Yi Tai , David P. Woodruff , Jason Zhang

This work initiates the study of memory-query tradeoffs for graph problems, with a focus on correlation clustering. Correlation clustering asks for a partition of the vertices that minimizes disagreements: non-edges inside clusters plus…

Computational Complexity · Computer Science 2026-05-25 Sumegha Garg , Songhua He , Periklis A. Papakonstantinou

We study fundamental limits of first-order stochastic optimization in a range of nonconvex settings, including L-smooth functions satisfying Quasar-Convexity (QC), Quadratic Growth (QG), and Restricted Secant Inequalities (RSI). While the…

Machine Learning · Statistics 2025-06-03 El Mehdi Saad , Wei-Cheng Lee , Francesco Orabona

Gaussian processes (GP) provide a prior over functions and allow finding complex regularities in data. Gaussian processes are successfully used for classification/regression problems and dimensionality reduction. In this work we consider…

Machine Learning · Computer Science 2016-11-21 Pavel Izmailov , Dmitry Kropotov