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We introduce linear probing hashing schemes that construct a hash table of size $n$, with constant load factor $\alpha$, on which the worst-case unsuccessful search time is asymptotically almost surely $O(\log \log n)$. The schemes employ…

Data Structures and Algorithms · Computer Science 2023-09-20 Ketan Dalal , Luc Devroye , Ebrahim Malalla

First introduced in 1954, linear probing is one of the oldest data structures in computer science, and due to its unrivaled data locality, it continues to be one of the fastest hash tables in practice. It is widely believed and taught,…

Data Structures and Algorithms · Computer Science 2021-07-06 Michael A. Bender , Bradley C. Kuszmaul , William Kuszmaul

Learned indexes leverage machine learning models to accelerate query answering in databases, showing impressive practical performance. However, theoretical understanding of these methods remains incomplete. Existing research suggests that…

Databases · Computer Science 2024-10-23 Luis Croquevielle , Guang Yang , Liang Liang , Ali Hadian , Thomas Heinis

In the last decade remarkable progress has been made in development of suitable proof techniques for analysing randomised search heuristics. The theoretical investigation of these algorithms on classes of functions is essential to the…

Neural and Evolutionary Computing · Computer Science 2020-10-22 Frank Neumann , Mojgan Pourhassan , Carsten Witt

We introduce a classical open-addressed hash table, called rainbow hashing, that supports a load factor of up to $1 - \varepsilon$, while also supporting $O(1)$ expected-time queries, and $O(\log \log \varepsilon^{-1})$ expected-time…

Data Structures and Algorithms · Computer Science 2024-09-18 Michael A. Bender , William Kuszmaul , Renfei Zhou

We analyze union-find using potential functions motivated by continuous algorithms, and give alternate proofs of the $O(\log\log{n})$, $O(\log^{*}n)$, $O(\log^{**}n)$, and $O(\alpha(n))$ amortized cost upper bounds. The proof of the…

Data Structures and Algorithms · Computer Science 2023-08-21 Zhiyi Huang , Chris Lambert , Zipei Nie , Richard Peng

In Linear Hashing ($\mathsf{LH}$) with $\beta$ bins on a size $u$ universe ${\mathcal{U}=\{0,1,\ldots, u-1\}}$, items $\{x_1,x_2,\ldots, x_n\}\subset \mathcal{U}$ are placed in bins by the hash function $$x_i\mapsto (ax_i+b)\mod p \mod…

Data Structures and Algorithms · Computer Science 2024-05-21 Alek Westover

Higher-Order Fixpoint Logic (HFL) is a hybrid of the simply typed \lambda-calculus and the modal \lambda-calculus. This makes it a highly expressive temporal logic that is capable of expressing various interesting correctness properties of…

Logic in Computer Science · Computer Science 2015-07-01 Roland Axelsson , Martin Lange , Rafal Somla

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

We study the conditions under which the convex relaxation of a mixed-integer linear programming formulation for ordered optimization problems, where sorting is part of the decision process, yields integral optimal solutions. Thereby solving…

Optimization and Control · Mathematics 2025-10-13 Víctor Blanco , Diego Laborda , Miguel Martínez-Antón

A matching in a graph is induced if no two of its edges are joined by an edge, and finding a large induced matching is a very hard problem. Lin et al. (Approximating weighted induced matchings, Discrete Applied Mathematics 243 (2018)…

Combinatorics · Mathematics 2018-12-17 Julien Baste , Maximilian Fürst , Dieter Rautenbach

Test-time compute scaling, the practice of spending extra computation during inference via repeated sampling, search, or extended reasoning, has become a powerful lever for improving large language model performance. Yet deploying these…

Machine Learning · Computer Science 2026-04-17 Zhiyuan Zhai , Bingcong Li , Bingnan Xiao , Ming Li , Xin Wang

For nearly six decades, the central open question in the study of hash tables has been to determine the optimal achievable tradeoff curve between time and space. State-of-the-art hash tables offer the following guarantee: If keys/values are…

Data Structures and Algorithms · Computer Science 2021-11-05 Michael A. Bender , Martín Farach-Colton , John Kuszmaul , William Kuszmaul , Mingmou Liu

We consider the hash function $h(x) = ((ax+b) \bmod p) \bmod n$ where $a,b$ are chosen uniformly at random from $\{0,1,\ldots,p-1\}$. We prove that when we use $h(x)$ in hashing with chaining to insert $n$ elements into a table of size $n$…

Data Structures and Algorithms · Computer Science 2017-06-12 Mathias Bæk Tejs Knudsen

Inference in log-linear models scales linearly in the size of output space in the worst-case. This is often a bottleneck in natural language processing and computer vision tasks when the output space is feasibly enumerable but very large.…

Machine Learning · Computer Science 2017-07-12 Stephen Mussmann , Daniel Levy , Stefano Ermon

Motivated by certain applications from physics, biochemistry, economics, and computer science, in which the objects under investigation are not accessible because of various limitations, we propose a trial-and-error model to examine…

Computational Complexity · Computer Science 2013-04-19 Xiaohui Bei , Ning Chen , Shengyu Zhang

Most hash tables have an insertion time of $O(1)$, possibly qualified as expected and/or amortised. While insertions into cuckoo hash tables indeed seem to take $O(1)$ expected time in practice, only polylogarithmic guarantees are proven in…

Data Structures and Algorithms · Computer Science 2022-04-26 Stefan Walzer

Cuckoo hashing is a highly practical dynamic dictionary: it provides amortized constant insertion time, worst case constant deletion time and lookup time, and good memory utilization. However, with a noticeable probability during the…

Data Structures and Algorithms · Computer Science 2009-03-04 Yuriy Arbitman , Moni Naor , Gil Segev

The simplex method for linear programming is known to be highly efficient in practice, and understanding its performance from a theoretical perspective is an active research topic. The framework of smoothed analysis, first introduced by…

Data Structures and Algorithms · Computer Science 2025-10-22 Sophie Huiberts , Yin Tat Lee , Xinzhi Zhang

We show that linear probing requires 5-independent hash functions for expected constant-time performance, matching an upper bound of [Pagh et al. STOC'07]. More precisely, we construct a 4-independent hash functions yielding expected…

Data Structures and Algorithms · Computer Science 2014-12-25 Mikkel Thorup
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