Results 11 to 20 of about 6,986 (292)

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

Sistemnì 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   +3 more sources

Approximate k -flat Nearest Neighbor Search [PDF]

Proceedings 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 $
Wolfgang Mulzer, Huy L. Nguyên, Paul Seiferth, Yannik Stein   +3 more
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Randomized Approximate Nearest Neighbor Search with Limited Adaptivity [PDF]

Proceedings 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].
Mingmou Liu, Xiaoyin Pan, Yitong Yin
openaire   +3 more sources

Approximate Nearest-Neighbor Search for Line Segments [PDF]

CoRR, 2021
Approximate nearest-neighbor search is a fundamental algorithmic problem that continues to inspire study due its essential role in numerous contexts. In contrast to most prior work, which has focused on point sets, we consider nearest-neighbor queries against a set of line segments in $\mathbb{R}^d$, for constant dimension $d$.
Abdelkader, Ahmed, Mount, David M.
openaire   +5 more sources

Approximate Nearest Neighbor Search with Window Filters

CoRR
We define and investigate the problem of $\textit{c-approximate window search}$: approximate nearest neighbor search where each point in the dataset has a numeric label, and the goal is to find nearest neighbors to queries within arbitrary label ranges.
Joshua Engels, Benjamin Landrum, Shangdi Yu, Laxman Dhulipala, Julian Shun   +4 more
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Fast Adaptive Approximate Nearest Neighbor Search with Cluster-Shaped Indices

Big Data and Cognitive Computing
In this study, we propose a novel adaptive algorithm for approximate nearest neighbor (ANN) search, based on the inverted file (IVF) index (cluster-based index) and online query complexity classification.
Vladimir Kazakovtsev, Mikhail Plekhanov, Alexandr Naumchev, Guzel Shkaberina, Igor Masich, Lyudmila Egorova, Alena Stupina, Aleksey Popov, Lev Kazakovtsev   +8 more
doaj   +2 more sources

SOAR: Improved Indexing for Approximate Nearest Neighbor Search

Advances in Neural Information Processing Systems 36, 2023
This paper introduces SOAR: Spilling with Orthogonality-Amplified Residuals, a novel data indexing technique for approximate nearest neighbor (ANN) search. SOAR extends upon previous approaches to ANN search, such as spill trees, that utilize multiple redundant representations while partitioning the data to reduce the probability of missing a nearest ...
Philip Sun, David Simcha, Dave Dopson, Ruiqi Guo, Sanjiv Kumar   +4 more
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Approximate Nearest Neighbor Search for Low Dimensional Queries [PDF]

Proceedings of the Twenty-Second Annual ACM-SIAM Symposium on Discrete Algorithms, 2011
We study the Approximate Nearest Neighbor problem for metric spaces where the query points are constrained to lie on a subspace of low doubling dimension, while the data is high-dimensional. We show that this problem can be solved efficiently despite the high dimensionality of the data.
Sariel Har-Peled, Nirman Kumar
openaire   +4 more sources

Efficient Autotuning of Hyperparameters in Approximate Nearest Neighbor Search [PDF]

, 2019
Accepted for the 23rd Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD ...
Elias Jääsaari, Ville Hyvönen, Teemu Roos   +2 more
openaire   +4 more sources

A Multilabel Classification Framework for Approximate Nearest Neighbor Search

Advances in Neural Information Processing Systems 35, 2022
Both supervised and unsupervised machine learning algorithms have been used to learn partition-based index structures for approximate nearest neighbor (ANN) search. Existing supervised algorithms formulate the learning task as finding a partition in which the nearest neighbors of a training set point belong to the same partition element as the point ...
Jääsaari Elias, Roos Teemu, Hyvönen Ville   +2 more
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