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Linear autoregressive models serve as basic representations of discrete time stochastic processes. Different attempts have been made to provide non-linear versions of the basic autoregressive process, including different versions based on…

Machine Learning · Statistics 2016-03-17 Edgar A. Valencia , Mauricio A. Álvarez

Growing demand for sustainable logistics and higher space utilization, driven by e-commerce and urbanization, increases the need for storage systems that are both energy- and space-efficient. Compact storage systems aim to maximize space…

Computational Complexity · Computer Science 2025-10-16 Malte Fliedner , Julian Golak , Yağmur Gül , Simone Neumann

Machine learning has been getting a large attention in the recent years, as a tool to process big data generated by ubiquitous sensors in our daily life. High speed, low energy computing machines are in demand to enable real-time artificial…

Machine Learning · Computer Science 2020-05-06 Zhong Sun , Giacomo Pedretti , Alessandro Bricalli , Daniele Ielmini

We propose a conceptually simple oblivious sort and oblivious random permutation algorithms called bucket oblivious sort and bucket oblivious random permutation. Bucket oblivious sort uses $6n\log n$ time (measured by the number of memory…

Data Structures and Algorithms · Computer Science 2021-04-30 Gilad Asharov , T-H. Hubert Chan , Kartik Nayak , Rafael Pass , Ling Ren , Elaine Shi

N-fold integer programming is a fundamental problem with a variety of natural applications in operations research and statistics. Moreover, it is universal and provides a new, variable-dimension, parametrization of all of integer…

Optimization and Control · Mathematics 2014-05-08 Raymond Hemmecke , Shmuel Onn , Lyubov Romanchuk

While well-known methods to list the intersections of either a list of segments or a complex polygon aim at achieving optimal time-complexity they often do so at the cost of memory comsumption and complex code. Real-life software…

Computational Geometry · Computer Science 2013-05-28 Jean Souviron

We present a new self-supervised machine learning approach for symbolic simplification of complex mathematical expressions. Training data is generated by scrambling simple expressions and recording the inverse operations, creating oracle…

High Energy Physics - Theory · Physics 2026-04-14 David Shih

Kernel methods are powerful tools in statistical learning, but their cubic complexity in the sample size n limits their use on large-scale datasets. In this work, we introduce a scalable framework for kernel regression with O(n log n)…

Machine Learning · Statistics 2025-09-04 Nathan Doumèche , Francis Bach , Gérard Biau , Claire Boyer

In this paper we propose a graph-based data clustering algorithm which is based on exact clustering of a minimum spanning tree in terms of a minimum isoperimetry criteria. We show that our basic clustering algorithm runs in $O(n \log n)$…

Computer Vision and Pattern Recognition · Computer Science 2012-03-20 Amir Daneshgar , Ramin Javadi , Basir Shariat Razavi

We study the problem of approximately simulating a $t$-step random walk on a graph where the input edges come from a single-pass stream. The straightforward algorithm using reservoir sampling needs $O(nt)$ words of memory. We show that this…

Data Structures and Algorithms · Computer Science 2020-01-03 Ce Jin

Recent rapid strides in memory safety tools and hardware have improved software quality and security. While coarse-grained memory safety has improved, achieving memory safety at the granularity of individual objects remains a challenge due…

Cryptography and Security · Computer Science 2019-06-11 Hiroshi Sasaki , Miguel A. Arroyo , M. Tarek Ibn Ziad , Koustubha Bhat , Kanad Sinha , Simha Sethumadhavan

Nowadays, various sensors are collecting, storing and transmitting tremendous trajectory data, and it is known that raw trajectory data seriously wastes the storage, network band and computing resource. Line simplification (LS) algorithms…

Databases · Computer Science 2017-02-21 Xuelian Lin , Shuai Ma , Han Zhang , Tianyu Wo , Jinpeng Huai

Consider laying out a fixed-topology tree of N nodes into external memory with block size B so as to minimize the worst-case number of block memory transfers required to traverse a path from the root to a node of depth D. We prove that the…

Data Structures and Algorithms · Computer Science 2013-11-28 Erik D. Demaine , John Iacono , Stefan Langerman

Link-based data structures, such as linked lists and binary search trees, have many well-known rearrangement steps allowing for efficient implementations of insertion, deletion, and other operations. We describe a rearrangement primitive…

Data Structures and Algorithms · Computer Science 2012-03-02 Boris Alexeev , M. Brian Jacokes

We consider the problem of augmenting an $n$-vertex tree with one shortcut in order to minimize the diameter of the resulting graph. The tree is embedded in an unknown space and we have access to an oracle that, when queried on a pair of…

Data Structures and Algorithms · Computer Science 2018-10-03 Davide Bilò

A hash table is said to be open-addressed (or non-obliviously open-addressed) if it stores elements (and free slots) in an array with no additional metadata. Intuitively, open-addressed hash tables must incur a space-time tradeoff: The…

Data Structures and Algorithms · Computer Science 2025-03-19 Michael A. Bender , William Kuszmaul , Renfei Zhou

A new model of causal failure is presented and used to solve a novel replica placement problem in data centers. The model describes dependencies among system components as a directed graph. A replica placement is defined as a subset of…

Data Structures and Algorithms · Computer Science 2017-01-09 K. Alex Mills , R. Chandrasekaran , Neeraj Mittal

Most of the attention in statistical compression is given to the space used by the compressed sequence, a problem completely solved with optimal prefix codes. However, in many applications, the storage space used to represent the prefix…

Data Structures and Algorithms · Computer Science 2015-06-30 Travis Gagie , Gonzalo Navarro , Yakov Nekrich , Alberto Ordóñez

The advent of memristive devices offers a promising avenue for efficient and scalable analog computing, particularly for linear algebra operations essential in various scientific and engineering applications. This paper investigates the…

Mesoscale and Nanoscale Physics · Physics 2025-06-23 Jonathan Lin , Frank Barrows , Francesco Caravelli

We develop a framework for resource efficient compilation of higher-level programs into lower-level reversible circuits. Our main focus is on optimizing the memory footprint of the resulting reversible networks. This is motivated by the…

Quantum Physics · Physics 2015-10-02 Alex Parent , Martin Roetteler , Krysta M. Svore