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Related papers: A Lower Bound for Dynamic Fractional Cascading

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Fractional cascading is one of the influential techniques in data structures, as it provides a general framework for solving the important iterative search problem. In the problem, the input is a graph $G$ with constant degree and a set of…

Computational Geometry · Computer Science 2020-11-30 Peyman Afshani , Pingan Cheng

We introduce the lazy search tree data structure. The lazy search tree is a comparison-based data structure on the pointer machine that supports order-based operations such as rank, select, membership, predecessor, successor, minimum, and…

Data Structures and Algorithms · Computer Science 2020-10-20 Bryce Sandlund , Sebastian Wild

Inspired by the classical fractional cascading technique, we introduce new techniques to speed up the following type of iterated search in 3D: The input is a graph $\mathbf{G}$ with bounded degree together with a set $H_v$ of 3D hyperplanes…

Computational Geometry · Computer Science 2025-04-11 Peyman Afshani , Yakov Nekrich , Frank Staals

This paper presents a general technique for optimally transforming any dynamic data structure that operates on atomic and indivisible keys by constant-time comparisons, into a data structure that handles unbounded-length keys whose…

Data Structures and Algorithms · Computer Science 2013-06-04 Amihood Amir , Gianni Franceschini , Roberto Grossi , Tsvi Kopelowitz , Moshe Lewenstein , Noa Lewenstein

A priority queue is a fundamental data structure that maintains a dynamic set of (key, priority)-pairs and supports Insert, Delete, ExtractMin and DecreaseKey operations. In the external memory model, the current best priority queue…

Data Structures and Algorithms · Computer Science 2018-06-21 Shunhua Jiang , Kasper Green Larsen

We consider the classical problem of representing a collection of priority queues under the operations \Findmin{}, \Insert{}, \Decrease{}, \Meld{}, \Delete{}, and \Deletemin{}. In the comparison-based model, if the first four operations are…

Data Structures and Algorithms · Computer Science 2011-12-06 Amr Elmasry , Jyrki Katajainen

We consider succinct data structures for representing a set of $n$ horizontal line segments in the plane given in rank space to support \emph{segment access}, \emph{segment selection}, and \emph{segment rank} queries. A segment access query…

Data Structures and Algorithms · Computer Science 2024-12-09 Philip Bille , Inge Li Gørtz , Simon R. Tarnow

The branch-and-bound algorithm based on decision diagrams introduced by Bergman et al. in 2016 is a framework for solving discrete optimization problems with a dynamic programming formulation. It works by compiling a series of bounded-width…

Data Structures and Algorithms · Computer Science 2024-01-19 Vianney Coppé , Xavier Gillard , Pierre Schaus

We build upon the recent papers by Weinstein and Yu (FOCS'16), Larsen (FOCS'12), and Clifford et al. (FOCS'15) to present a general framework that gives amortized lower bounds on the update and query times of dynamic data structures. Using…

Data Structures and Algorithms · Computer Science 2019-02-07 Sayan Bhattacharya , Monika Henzinger , Stefan Neumann

We give new deterministic bounds for fully-dynamic graph connectivity. Our data structure supports updates (edge insertions/deletions) in $O(\log^2n/\log\log n)$ amortized time and connectivity queries in $O(\log n/\log\log n)$ worst-case…

Data Structures and Algorithms · Computer Science 2012-09-26 Christian Wulff-Nilsen

We develop a new technique for proving cell-probe lower bounds on dynamic data structures. This technique enables us to prove an amortized randomized Omega(lg n) lower bound per operation for several data structural problems on n elements,…

Data Structures and Algorithms · Computer Science 2007-05-23 Mihai Patrascu , Erik D. Demaine

We present an optimal partially-persistent external-memory search tree with amortized I/O bounds matching those achieved by the non-persistent $B^{\varepsilon}$-tree by Brodal and Fagerberg [SODA 2003]. In a partially-persistent data…

Data Structures and Algorithms · Computer Science 2025-03-12 Gerth Stølting Brodal , Casper Moldrup Rysgaard , Rolf Svenning

Modern tracking technology has made the collection of large numbers of densely sampled trajectories of moving objects widely available. We consider a fundamental problem encountered when analysing such data: Given $n$ polygonal curves $S$…

Computational Geometry · Computer Science 2017-07-18 Peyman Afshani , Anne Driemel

Compressed indexing is a powerful technique that enables efficient querying over data stored in compressed form, significantly reducing memory usage and often accelerating computation. While extensive progress has been made for…

Data Structures and Algorithms · Computer Science 2025-10-23 Rajat De , Dominik Kempa

The B-tree is a fundamental secondary index structure that is widely used for answering one-dimensional range reporting queries. Given a set of $N$ keys, a range query can be answered in $O(\log_B \nm + \frac{K}{B})$ I/Os, where $B$ is the…

Data Structures and Algorithms · Computer Science 2008-11-27 Ke Yi

In this paper we present new data structures for two extensively studied variants of the orthogonal range searching problem. First, we describe a data structure that supports two-dimensional orthogonal range minima queries in $O(n)$ space…

Data Structures and Algorithms · Computer Science 2020-07-23 Yakov Nekrich

In this work, we study the limits of compressed data structures, i.e., structures that support various queries on an input text $T\in\Sigma^n$ using space proportional to the size of $T$ in compressed form. Nearly all fundamental queries…

Data Structures and Algorithms · Computer Science 2025-10-23 Dominik Kempa , Tomasz Kociumaka

In the particular case we have insertions/deletions at the tail of a given set S of $n$ one-dimensional elements, we present a simpler and more concrete algorithm than that presented in [Anderson, 2007] achieving the same (but also…

Data Structures and Algorithms · Computer Science 2008-12-18 Spyros Sioutas

Retrieval data structures are data structures that answer key-value queries without paying the space overhead of explicitly storing keys. The problem can be formulated in four settings (static, value-dynamic, incremental, or dynamic), each…

Data Structures and Algorithms · Computer Science 2024-10-25 William Kuszmaul , Aaron Putterman , Tingqiang Xu , Hangrui Zhou , Renfei Zhou

In this paper, a new and novel data structure is proposed to dynamically insert and delete segments. Unlike the standard segment trees[3], the proposed data structure permits insertion of a segment with interval range beyond the interval…

Computational Geometry · Computer Science 2015-01-15 K. S. Easwarakumar , T. Hema
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