Results 11 to 20 of about 70,489 (181)

Semi-supervised inverted file index approach for approximate nearest neighbor search

open access: yesSistemnì Doslìdženâ ta Informacìjnì Tehnologìï, 2023
This paper introduces a novel modification to the Inverted File (IVF) index approach for approximate nearest neighbor search, incorporating supervised learning techniques to enhance the efficacy of intermediate clustering and achieve more balanced ...
Anton Bazdyrev
doaj   +1 more source

Secure and efficient approximate nearest neighbors search [PDF]

open access: yesProceedings of the first ACM workshop on Information hiding and multimedia security, 2013
This paper presents a moderately secure but very efficient approximate nearest neighbors search. After detailing the threats pertaining to the "honest but curious" model, our approach starts from a state-of-the-art algorithm in the domain of approximate nearest neighbors search. We gradually develop mechanisms partially blocking the attacks threatening
Mathon, Benjamin   +3 more
openaire   +1 more source

Approximate k -flat Nearest Neighbor Search [PDF]

open access: yesProceedings of the forty-seventh annual ACM symposium on Theory of Computing, 2015
Let $k$ be a nonnegative integer. In the approximate $k$-flat nearest neighbor ($k$-ANN) problem, we are given a set $P \subset \mathbb{R}^d$ of $n$ points in $d$-dimensional space and a fixed approximation factor $c > 1$. Our goal is to preprocess $P$ so that we can efficiently answer approximate $k$-flat nearest neighbor queries: given a $k$-flat $
Mulzer, Wolfgang   +3 more
openaire   +2 more sources

APPROXIMATE NEAREST NEIGHBOR SEARCH IN HIGH DIMENSIONS [PDF]

open access: yesProceedings of the International Congress of Mathematicians (ICM 2018), 2019
27 pages, no figures; to appear in the proceedings of ICM 2018 (accompanying the talk by P. Indyk)
Andoni, Alexandr   +2 more
openaire   +3 more sources

Approximate Nearest Neighbor Search on Standard Search Engines

open access: yes, 2022
Approximate search for high-dimensional vectors is commonly addressed using dedicated techniques often combined with hardware acceleration provided by GPUs, FPGAs, and other custom in-memory silicon. Despite their effectiveness, harmonizing those optimized solutions with other types of searches often poses technological difficulties.
Carrara F   +3 more
openaire   +3 more sources

Improving Natural Language Person Description Search from Videos with Language Model Fine-Tuning and Approximate Nearest Neighbor

open access: yesBig Data and Cognitive Computing, 2022
Due to the ubiquitous nature of CCTV cameras that record continuously, there is a large amount of video data that are unstructured. Often, when these recordings have to be reviewed, it is to look for a specific person that fits a certain description ...
Sumeth Yuenyong   +1 more
doaj   +1 more source

Randomized Approximate Nearest Neighbor Search with Limited Adaptivity [PDF]

open access: yesProceedings of the 28th ACM Symposium on Parallelism in Algorithms and Architectures, 2016
We study the complexity of parallel data structures for approximate nearest neighbor search in d -dimensional Hamming space {0,1} d . A classic model for static data structures is the cell-probe model [27].
Liu, Mingmou, Pan, Xiaoyin, Yin, Yitong
openaire   +2 more sources

KNN Algorithm of Enhanced Clustering Based on Density Canopy and Deep Feature

open access: yesJisuanji kexue yu tansuo, 2021
As the most widely used supervised classification algorithm, K nearest neighbor (KNN) algorithm is often inefficient in the processing of large-scale and multidimensional data.
SHEN Xueli, QIN Xinyu
doaj   +1 more source

RPA: a memory-efficient metric-space recall@R ANNS index

open access: yesShenzhen Daxue xuebao. Ligong ban, 2023
Approximate nearest neighbor search (ANNS) for high dimensional data has received extensive research efforts. Many existing ANNS methods in metric spaces are essentially based on the permutation of pivots, or pre-selected reference points, which are ...
JIANG Runben, CHEN Jiaying, MAO Rui
doaj   +1 more source

Hardness of approximate nearest neighbor search [PDF]

open access: yesProceedings of the 50th Annual ACM SIGACT Symposium on Theory of Computing, 2018
We prove conditional near-quadratic running time lower bounds for approximate Bichromatic Closest Pair with Euclidean, Manhattan, Hamming, or edit distance. Specifically, unless the Strong Exponential Time Hypothesis (SETH) is false, for every $ >0$ there exists a constant $ >0$ such that computing a $(1+ )$-approximation to the Bichromatic ...
openaire   +2 more sources

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