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Clustering is widely used in different field such as biology, psychology, and economics. Most traditional clustering algorithms are limited to handling datasets that contain either numeric or categorical attributes. However, datasets with…

Databases · Computer Science 2019-07-03 Trupti M. Kodinariya Dr. Prashant R. Makwana

Inverted file structure is a common technique for accelerating dense retrieval. It clusters documents based on their embeddings; during searching, it probes nearby clusters w.r.t. an input query and only evaluates documents within them by…

Information Retrieval · Computer Science 2023-10-18 Peitian Zhang , Zheng Liu , Shitao Xiao , Zhicheng Dou , Jing Yao

Incorporating a deep generative model as the prior distribution in inverse problems has established substantial success in reconstructing images from corrupted observations. Notwithstanding, the existing optimization approaches use gradient…

Machine Learning · Computer Science 2023-01-31 Tianci Liu , Tong Yang , Quan Zhang , Qi Lei

In this paper we investigate the problem of partitioning an input string T in such a way that compressing individually its parts via a base-compressor C gets a compressed output that is shorter than applying C over the entire T at once.…

Data Structures and Algorithms · Computer Science 2009-06-26 Paolo Ferragina , Igor Nitto , Rossano Venturini

Many new database application domains such as experimental sciences and medicine are characterized by large sequences as their main form of data. Using approximate representation can significantly reduce the required storage and search…

Databases · Computer Science 2019-04-22 Hagit Shatkay , Stanley B. Zdonik

Within the replica framework we study analytically the instance space of the number partitioning problem. This classic integer programming problem consists of partitioning a sequence of N positive real numbers $\{a_1, a_2,..., a_N}$ (the…

Condensed Matter · Physics 2009-10-31 F. F. Ferreira , J. F. Fontanari

Image instance retrieval is the problem of retrieving images from a database which contain the same object. Convolutional Neural Network (CNN) based descriptors are becoming the dominant approach for generating {\it global image…

Computer Vision and Pattern Recognition · Computer Science 2017-01-19 Vijay Chandrasekhar , Jie Lin , Qianli Liao , Olivier Morère , Antoine Veillard , Lingyu Duan , Tomaso Poggio

The Suffix Array is a classic text index enabling on-line pattern matching queries via simple binary search. The main drawback of the Suffix Array is that it takes linear space in the text's length, even if the text itself is extremely…

Data Structures and Algorithms · Computer Science 2025-03-19 Davide Cenzato , Lore Depuydt , Travis Gagie , Sung-Hwan Kim , Giovanni Manzini , Francisco Olivares , Nicola Prezza

String sorting is an important part of tasks such as building index data structures. Unfortunately, current string sorting algorithms do not scale to massively parallel distributed-memory machines since they either have latency (at least)…

Data Structures and Algorithms · Computer Science 2024-04-26 Florian Kurpicz , Pascal Mehnert , Peter Sanders , Matthias Schimek

The $r$-index (Gagie et al., JACM 2020) represented a breakthrough in compressed indexing of repetitive text collections, outperforming its alternatives by orders of magnitude. Its space usage, $\mathcal{O}(r)$ where $r$ is the number of…

Data Structures and Algorithms · Computer Science 2021-03-30 Dustin Cobas , Travis Gagie , Gonzalo Navarro

The direct application of the definition of sorting in lattices is impractical because it leads to an algorithm with exponential complexity. In this paper we present for distributive lattices a recursive formulation to compute the sort of a…

Discrete Mathematics · Computer Science 2013-06-04 Jens Gerlach

Dimension reduction is widely regarded as an effective way for decreasing the computation, storage and communication loads of data-driven intelligent systems, leading to a growing demand for statistical methods that allow analysis (e.g.,…

Computer Vision and Pattern Recognition · Computer Science 2019-08-23 Guangcan Liu , Zhao Zhang , Qingshan Liu , Kongkai Xiong

Inspired by the classical fractional cascading technique, we introduce new techniques to speed up the following type of iterated search in 3D: The input is a graph $\mathbf{G}$ with bounded degree together with a set $H_v$ of 3D hyperplanes…

Computational Geometry · Computer Science 2025-04-11 Peyman Afshani , Yakov Nekrich , Frank Staals

Integer partitions are deeply related to many phenomena in statistical physics. A question naturally arises which is of interest to physics both on "purely" theoretical and on practical, computational grounds. Is it possible to apprehend…

Computational Physics · Physics 2007-05-23 N. M. Chase

We present an acceleration method for sequences of large-scale linear systems, such as the ones arising from the numerical solution of time-dependent partial differential equations coupled with algebraic constraints. We discuss different…

Numerical Analysis · Mathematics 2024-03-29 Margherita Guido , Daniel Kressner , Paolo Ricci

In a dynamic retrieval system, documents must be ingested as they arrive, and be immediately findable by queries. Our purpose in this paper is to describe an index structure and processing regime that accommodates that requirement for…

Information Retrieval · Computer Science 2023-01-12 Alistair Moffat , Joel Mackenzie

Query Segmentation is one of the critical components for understanding users' search intent in Information Retrieval tasks. It involves grouping tokens in the search query into meaningful phrases which help downstream tasks like search…

Information Retrieval · Computer Science 2017-07-26 Ajinkya Kale , Thrivikrama Taula , Sanjika Hewavitharana , Amit Srivastava

Given an array $X$ of $N+1$ strictly ordered floating point numbers and a floating point number $z$ in the interval $[X_0,X_N)$, a common problem is to find the index $i$ of the interval $[X_{i},X_{i+1})$ containing $z$. This problem arises…

Data Structures and Algorithms · Computer Science 2017-12-01 Fabio Cannizzo

Large-scale optimization problems that seek sparse solutions have become ubiquitous. They are routinely solved with various specialized first-order methods. Although such methods are often fast, they usually struggle with not-so-well…

Optimization and Control · Mathematics 2021-11-29 Valentina De Simone , Daniela di Serafino , Jacek Gondzio , Spyridon Pougkakiotis , Marco Viola

Model compression has gained significant popularity as a means to alleviate the computational and memory demands of machine learning models. Each compression technique leverages unique features to reduce the size of neural networks.…

Machine Learning · Computer Science 2024-08-20 Yingtao Shen , Minqing Sun , Jianzhe Lin , Jie Zhao , An Zou