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The Distributed Bloom Filter is a space-efficient, probabilistic data structure designed to perform more efficient set reconciliations in distributed systems. It guarantees eventual consistency of states between nodes in a system, while…

Data Structures and Algorithms · Computer Science 2020-02-20 Lum Ramabaja , Arber Avdullahu

Simple semitoric systems were classified about ten years ago in terms of a collection of invariants, essentially given by a convex polygon with some marked points corresponding to focus-focus singularities. Each marked point is endowed with…

Symplectic Geometry · Mathematics 2020-02-14 Álvaro Pelayo

The DifSets package for GAP implements an algorithm for enumerating all difference sets in a group up to equivalence and provides access to a library of results. The algorithm functions by finding difference sums, which are potential images…

Combinatorics · Mathematics 2019-10-16 Dylan Peifer

Each time-series has its own linear trend, the directionality of a timeseries, and removing the linear trend is crucial to get the more intuitive matching results. Supporting the linear detrending in subsequence matching is a challenging…

Databases · Computer Science 2015-05-19 Myeong-Seon Gil , Yang-Sae Moon , Bum-Soo Kim

Applications in various domains rely on processing graph streams, e.g., communication logs of a cloud-troubleshooting system, road-network traffic updates, and interactions on a social network. A labeled-graph stream refers to a sequence of…

Databases · Computer Science 2017-09-21 Mohamed S. Hassan , Bruno Ribeiro , Walid G. Aref

Data sketches are approximate succinct summaries of long streams. They are widely used for processing massive amounts of data and answering statistical queries about it in real-time. Existing libraries producing sketches are very fast, but…

Data Structures and Algorithms · Computer Science 2019-12-06 Arik Rinberg , Alexander Spiegelman , Edward Bortnikov , Eshcar Hillel , Idit Keidar , Lee Rhodes , Hadar Serviansky

Streaming computation plays an important role in large-scale data analysis. The sliding window model is a model of streaming computation which also captures the recency of the data. In this model, data arrives one item at a time, but only…

Data Structures and Algorithms · Computer Science 2021-11-01 Alessandro Epasto , Mohammad Mahdian , Vahab Mirrokni , Peilin Zhong

This paper defines the notion of class discrepancy for families of functions. It shows that low discrepancy classes admit small offline and streaming coresets. We provide general techniques for bounding the class discrepancy of machine…

Machine Learning · Computer Science 2019-06-13 Zohar Karnin , Edo Liberty

The efficacy of zero-shot sketch-based image retrieval (ZS-SBIR) models is governed by two challenges. The immense distributions-gap between the sketches and the images requires a proper domain alignment. Moreover, the fine-grained nature…

Computer Vision and Pattern Recognition · Computer Science 2022-01-19 Ushasi Chaudhuri , Ruchika Chavan , Biplab Banerjee , Anjan Dutta , Zeynep Akata

We consider the problem of succinctly encoding a static map to support approximate queries. We derive upper and lower bounds on the space requirements in terms of the error rate and the entropy of the distribution of values over keys: our…

Data Structures and Algorithms · Computer Science 2007-10-18 David Talbot , John Talbot

In this paper we introduce a new class of diffeomorphic smoothers based on general spline smoothing techniques and on the use of some tools that have been recently developed in the context of image warping to compute smooth diffeomorphisms.…

Statistics Theory · Mathematics 2009-12-07 Jeremie bigot , Sebastien Gadat

We live in a dynamic world where things change all the time. Given two images of the same scene, being able to automatically detect the changes in them has practical applications in a variety of domains. In this paper, we tackle the change…

Computer Vision and Pattern Recognition · Computer Science 2022-09-30 Ragav Sachdeva , Andrew Zisserman

Kernel estimation techniques, such as mean shift, suffer from one major drawback: the kernel bandwidth selection. The bandwidth can be fixed for all the data set or can vary at each points. Automatic bandwidth selection becomes a real…

Computer Vision and Pattern Recognition · Computer Science 2011-11-10 Aurelie Bugeau , Patrick Pérez

Pairwise alignment of DNA sequencing data is a ubiquitous task in bioinformatics and typically represents a heavy computational burden. A standard approach to speed up this task is to compute "sketches" of the DNA reads (typically via…

Information Theory · Computer Science 2021-07-12 Ilan Shomorony , Govinda M. Kamath

We propose a diffusion-based inverse rendering framework that decomposes a single RGB image into geometry, material, and lighting. Inverse rendering is inherently ill-posed, making it difficult to predict a single accurate solution. To…

Computer Vision and Pattern Recognition · Computer Science 2025-03-14 JunYong Choi , Min-Cheol Sagong , SeokYeong Lee , Seung-Won Jung , Ig-Jae Kim , Junghyun Cho

Symmetry in differential equations reveals invariances and offers a powerful means to reduce model complexity. Lie group analysis characterizes these symmetries through infinitesimal generators, which provide a local, linear criterion for…

Numerical Analysis · Mathematics 2025-11-14 Max Kreider , John Harlim , Daning Huang

Persistence diagrams, combining geometry and topology for an effective shape description used in pattern recognition, have already proven to be an effective tool for shape representation with respect to a certainfiltering function.…

Algebraic Topology · Mathematics 2018-12-26 Alessia Angeli , Massimo Ferri , Ivan Tomba

We survey the role of symmetry in diffeomorphic registration of landmarks, curves, surfaces, images and higher-order data. The infinite dimensional problem of finding correspondences between objects can for a range of concrete data types be…

Computer Vision and Pattern Recognition · Computer Science 2014-12-25 Stefan Sommer , Henry O. Jacobs

By approximating posterior distributions with weighted samples, particle filters (PFs) provide an efficient mechanism for solving non-linear sequential state estimation problems. While the effectiveness of particle filters has been…

Machine Learning · Computer Science 2023-12-15 Xiongjie Chen , Yunpeng Li

The need for scalable concurrent ordered set data structures with linearizable range query support is increasing due to the rise of multicore computers, data processing platforms and in-memory databases. This paper presents a new concurrent…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-09-05 Kjell Winblad