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Low-rank approximation in data streams is a fundamental and significant task in computing science, machine learning and statistics. Multiple streaming algorithms have emerged over years and most of them are inspired by randomized…

Data Structures and Algorithms · Computer Science 2022-09-30 Cuiyu Liu , Chuanfu Xiao , Mingshuo Ding , Chao Yang

The remarkable successes of neural networks in a huge variety of inverse problems have fueled their adoption in disciplines ranging from medical imaging to seismic analysis over the past decade. However, the high dimensionality of such…

Machine Learning · Statistics 2023-10-11 Santhosh Karnik , Rongrong Wang , Mark Iwen

Normalizing flows have grown more popular over the last few years; however, they continue to be computationally expensive, making them difficult to be accepted into the broader machine learning community. In this paper, we introduce a…

Machine Learning · Computer Science 2021-12-15 Achintya Gopal

Datasets with sheer volume have been generated from fields including computer vision, medical imageology, and astronomy whose large-scale and high-dimensional properties hamper the implementation of classical statistical models. To tackle…

Statistics Theory · Mathematics 2023-05-30 Hang Yu , Zhenxing Dou , Zhiwei Chen , Xiaomeng Yan

The distinct elements problem is one of the fundamental problems in streaming algorithms --- given a stream of integers in the range $\{1,\ldots,n\}$, we wish to provide a $(1+\varepsilon)$ approximation to the number of distinct elements…

Data Structures and Algorithms · Computer Science 2019-01-07 Jarosław Błasiok

Maximizing a monotone submodular function under various constraints is a classical and intensively studied problem. However, in the single-pass streaming model, where the elements arrive one by one and an algorithm can store only a small…

Data Structures and Algorithms · Computer Science 2020-02-14 Chien-Chung Huang , Naonori Kakimura , Simon Mauras , Yuichi Yoshida

The maximum coverage problem is to select $k$ sets from a collection of sets such that the cardinality of the union of the selected sets is maximized. We consider $(1-1/e-\epsilon)$-approximation algorithms for this NP-hard problem in three…

Data Structures and Algorithms · Computer Science 2024-03-22 Amit Chakrabarti , Andrew McGregor , Anthony Wirth

We study streaming algorithms for the interval selection problem: finding a maximum cardinality subset of disjoint intervals on the line. A deterministic 2-approximation streaming algorithm for this problem is developed, together with an…

Data Structures and Algorithms · Computer Science 2015-03-20 Yuval Emek , Magnus M. Halldorsson , Adi Rosen

There has been a recent explosion in the size of stored data, partially due to advances in storage technology, and partially due to the growing popularity of cloud-computing and the vast quantities of data generated. This motivates the need…

Data Structures and Algorithms · Computer Science 2012-12-06 Isabelle Stanton

We study the communication complexity and streaming complexity of approximating unweighted semi-matchings. A semi-matching in a bipartite graph G = (A, B, E), with n = |A|, is a subset of edges S that matches all A vertices to B vertices…

Data Structures and Algorithms · Computer Science 2013-04-26 Christian Konrad , Adi Rosén

We consider the problem of approximating a given matrix by a low-rank matrix so as to minimize the entrywise $\ell_p$-approximation error, for any $p \geq 1$; the case $p = 2$ is the classical SVD problem. We obtain the first provably good…

Data Structures and Algorithms · Computer Science 2017-05-19 Flavio Chierichetti , Sreenivas Gollapudi , Ravi Kumar , Silvio Lattanzi , Rina Panigrahy , David P. Woodruff

Computing the proximal operator of the $\ell_\infty$ norm, $\textbf{prox}_{\alpha ||\cdot||_\infty}(\mathbf{x})$, generally requires a sort of the input data, or at least a partial sort similar to quicksort. In order to avoid using a sort,…

Numerical Analysis · Mathematics 2024-08-22 Kathryn Linehan , Radu Balan

In many emerging applications, data streams are monitored in a network environment. Due to limited communication bandwidth and other resource constraints, a critical and practical demand is to online compress data streams continuously with…

Data Structures and Algorithms · Computer Science 2008-12-01 Emad Soroush , Kui Wu , Jian Pei

In this paper, we extend the methodology developed for Support Vector Machines (SVM) using $\ell_2$-norm ($\ell_2$-SVM) to the more general case of $\ell_p$-norms with $p\ge 1$ ($\ell_p$-SVM). The resulting primal and dual problems are…

Optimization and Control · Mathematics 2021-01-12 Víctor Blanco , Justo Puerto , Antonio M. Rodríguez-Chía

The study of parameterized streaming complexity on graph problems was initiated by Fafianie et al. (MFCS'14) and Chitnis et al. (SODA'15 and SODA'16). Simply put, the main goal is to design streaming algorithms for parameterized problems…

Computational Complexity · Computer Science 2019-10-03 Arijit Bishnu , Arijit Ghosh , Sudeshna Kolay , Gopinath Mishra , Saket Saurabh

Recent advancements in real-time super-resolution have enabled higher-quality video streaming, yet existing methods struggle with the unique challenges of compressed video content. Commonly used datasets do not accurately reflect the…

Computer Vision and Pattern Recognition · Computer Science 2026-02-17 Evgeney Bogatyrev , Khaled Abud , Ivan Molodetskikh , Nikita Alutis , Dmitriy Vatolin

The efficient estimation of frequency moments of a data stream in one-pass using limited space and time per item is one of the most fundamental problem in data stream processing. An especially important estimation is to find the number of…

Data Structures and Algorithms · Computer Science 2010-10-29 Gokarna Sharma , Costas Busch , Srikanta Tirthapura

We initiate a study of the streaming complexity of constraint satisfaction problems (CSPs) when the constraints arrive in a random order. We show that there exists a CSP, namely $\textsf{Max-DICUT}$, for which random ordering makes a…

Data Structures and Algorithms · Computer Science 2023-04-14 Raghuvansh R. Saxena , Noah Singer , Madhu Sudan , Santhoshini Velusamy

Given a stream $x_1,x_2,\dots,x_n$ of items from a Universe $U$ of size poly$(n)$, and a parameter $\epsilon>0$, an item $i\in U$ is said to be an $\ell_2$ heavy hitter if its frequency $f_i$ in the stream is at least $\sqrt{\epsilon F_2}$,…

Data Structures and Algorithms · Computer Science 2026-02-10 Santhoshini Velusamy , Huacheng Yu

In Euclidean Uniform Facility Location (UFL), the input is a set of clients in $\mathbb{R}^d$ and the goal is to place facilities to serve them, so as to minimize the total cost of opening facilities plus connecting the clients. We study…

Data Structures and Algorithms · Computer Science 2023-01-31 Artur Czumaj , Arnold Filtser , Shaofeng H. -C. Jiang , Robert Krauthgamer , Pavel Veselý , Mingwei Yang
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