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The sliding window model of computation captures scenarios in which data are continually arriving in the form of a stream, and only the most recent $w$ items are used for analysis. In this setting, an algorithm needs to accurately track…

Cryptography and Security · Computer Science 2024-06-13 Yiping Wang , Yanhao Wang , Cen Chen

Network monitoring is vital in modern clouds and data center networks for traffic engineering, network diagnosis, network intrusion detection, which need diverse traffic statistics ranging from flow size distributions to heavy hitters. To…

Networking and Internet Architecture · Computer Science 2019-05-09 Yongquan Fu , Dongsheng Li , Siqi Shen , Yiming Zhang , Kai Chen

Hatching is a common method used by artists to accentuate the third dimension of a sketch, and to illuminate the scene. Our system SHAD3S attempts to compete with a human at hatching generic three-dimensional (3D) shapes, and also tries to…

Graphics · Computer Science 2021-09-07 Raghav B. Venkataramaiyer , Abhishek Joshi , Saisha Narang , Vinay P. Namboodiri

Tensor network methods provide a scalable solution to represent high-dimensional data. However, their efficacy is often limited by static, expert-defined structures that fail to adapt to evolving data correlations. We address this…

Computational Engineering, Finance, and Science · Computer Science 2026-03-31 Zheng Guo , Aditya Deshpande , Xinyu Wang , Brian C. Kiedrowski , Alex A. Gorodetsky

This survey highlights the recent advances in algorithms for numerical linear algebra that have come from the technique of linear sketching, whereby given a matrix, one first compresses it to a much smaller matrix by multiplying it by a…

Data Structures and Algorithms · Computer Science 2015-02-11 David P. Woodruff

Personalization techniques for large text-to-image (T2I) models allow users to incorporate new concepts from reference images. However, existing methods primarily rely on textual descriptions, leading to limited control over customized…

Computer Vision and Pattern Recognition · Computer Science 2024-02-28 Chufeng Xiao , Hongbo Fu

The Count-Min sketch is an important and well-studied data summarization method. It allows one to estimate the count of any item in a stream using a small, fixed size data sketch. However, the accuracy of the sketch depends on…

Data Structures and Algorithms · Computer Science 2018-11-13 Daniel Ting

We consider the problem of sketching set valuation functions, defined as the expectation of a valuation function applied to independent random item values. For valuation functions that are monotone and either subadditive or submodular, and…

Statistics Theory · Mathematics 2026-03-11 Milan Vojnović , Yiliu Wang

Large-scale distributed training of neural networks is often limited by network bandwidth, wherein the communication time overwhelms the local computation time. Motivated by the success of sketching methods in sub-linear/streaming…

Machine Learning · Computer Science 2020-01-24 Nikita Ivkin , Daniel Rothchild , Enayat Ullah , Vladimir Braverman , Ion Stoica , Raman Arora

With the continuous increase in the number and resolution of video surveillance cameras, the burden of transmitting and storing surveillance video is growing. Traditional communication methods based on Shannon's theory are facing…

Computer Vision and Pattern Recognition · Computer Science 2025-05-13 Baoping Cheng , Yukun Zhang , Liming Wang , Xiaoyan Xie , Tao Fu , Dongkun Wang , Xiaoming Tao

Generating sketches with specific patterns as expected, i.e., manipulating sketches in a controllable way, is a popular task. Recent studies control sketch features at stroke-level by editing values of stroke embeddings as conditions.…

Computer Vision and Pattern Recognition · Computer Science 2026-03-23 Sicong Zang , Shuhui Gao , Zhijun Fang

Memory and network bandwidth are decisive bottlenecks when handling high-resolution multidimensional data sets in visualization applications, and they increasingly demand suitable data compression strategies. We introduce a novel lossy…

Graphics · Computer Science 2019-03-12 Rafael Ballester-Ripoll , Peter Lindstrom , Renato Pajarola

LiveSketch is a novel algorithm for searching large image collections using hand-sketched queries. LiveSketch tackles the inherent ambiguity of sketch search by creating visual suggestions that augment the query as it is drawn, making query…

Computer Vision and Pattern Recognition · Computer Science 2019-04-16 John Collomosse , Tu Bui , Hailin Jin

In this paper, we introduce a sketching algorithm for constructing a tensor train representation of a probability density from its samples. Our method deviates from the standard recursive SVD-based procedure for constructing a tensor train.…

Numerical Analysis · Mathematics 2023-06-27 YH. Hur , J. G. Hoskins , M. Lindsey , E. M. Stoudenmire , Y. Khoo

In data stream applications, one of the critical issues is to estimate the frequency of each item in the specific multiset. The multiset means that each item in this set can appear multiple times. The data streams in many applications are…

Data Structures and Algorithms · Computer Science 2020-01-07 Ning Li

We propose RTSMS (Randomized Tucker via Single-Mode-Sketching), a randomized algorithm for approximately computing a low-rank Tucker decomposition of a given tensor. It uses sketching and least-squares to compute the Tucker decomposition in…

Numerical Analysis · Mathematics 2023-11-28 Behnam Hashemi , Yuji Nakatsukasa

We present a sketch-based CAD modeling system, where users create objects incrementally by sketching the desired shape edits, which our system automatically translates to CAD operations. Our approach is motivated by the close similarities…

Graphics · Computer Science 2020-09-11 Changjian Li , Hao Pan , Adrien Bousseau , Niloy J. Mitra

Sketch-based shape modeling aims to bridge the gap between 2D drawing and 3D modeling by providing an intuitive and accessible approach to create 3D shapes from 2D sketches. However, existing methods still suffer from limitations in…

Graphics · Computer Science 2023-09-13 Jie Zhou , Zhongjin Luo , Qian Yu , Xiaoguang Han , Hongbo Fu

We propose a new randomized algorithm for solving L2-regularized least-squares problems based on sketching. We consider two of the most popular random embeddings, namely, Gaussian embeddings and the Subsampled Randomized Hadamard Transform…

Machine Learning · Computer Science 2020-10-26 Jonathan Lacotte , Mert Pilanci

Recently, randomly mapping vectorial data to strings of discrete symbols (i.e., sketches) for fast and space-efficient similarity searches has become popular. Such random mapping is called similarity-preserving hashing and approximates a…

Machine Learning · Computer Science 2019-10-21 Shunsuke Kanda , Yasuo Tabei