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Quantization to speedup approximate nearest neighbor search
The quantization-based approaches not only are the effective methods for solving the problems of approximate nearest neighbor search, but also...
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Flexible product quantization for fast approximate nearest neighbor search
Product quantization (PQ) is an effective solution to approximate nearest neighbor (ANN) search. The idea of PQ is to decompose the space into...
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An efficient indexing technique for billion-scale nearest neighbor search
Approximate nearest neighbor search is an indispensable component in many computer vision applications. To index more data, such as images, on one...
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Fast Hubness-Reduced Nearest Neighbor Search for Entity Alignment in Knowledge Graphs
The flexibility of Knowledge Graphs to represent heterogeneous entities and relations of many types is challenging for conventional data integration...
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Accelerating massive queries of approximate nearest neighbor search on high-dimensional data
Approximate nearest neighbor (ANN) search on high-dimensional data is a fundamental operation in many applications. In this paper, we study massive...
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Secure Approximate Nearest Neighbor Search with Locality-Sensitive Hashing
Ensuring both security and efficiency in Nearest Neighbor Search (NNS) on large datasets remains a formidable challenge, as it often leads to...
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Twin neural network improved k-nearest neighbor regression
Twin neural network regression is trained to predict the difference between the regression targets of two data points rather than the individual...
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Learning-based query optimization for multi-probe approximate nearest neighbor search
Approximate nearest neighbor search (ANNS) is a fundamental problem that has attracted widespread attention for decades. Multi-probe ANNS is one of...
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DISCONA: distributed sample compression for nearest neighbor algorithm
Sample compression using 𝜖 -net effectively reduces the number of labeled instances required for accurate classification with nearest neighbor...
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Approximate nearest neighbor for long document relationship labeling in digital libraries
Relationship tagging of long text documents is a growing need in information science, spurred by the emergence of multi-million book bibliographic...
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Revisiting Nearest-Neighbor-Based Information Set Decoding
The syndrome decoding problem lies at the heart of code-based cryptographic constructions. Information Set Decoding (ISD) algorithms are commonly...
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Turbo Scan: Fast Sequential Nearest Neighbor Search in High Dimensions
This paper introduces Turbo Scan (TS), a novel k-nearest neighbor search solution tailored for high-dimensional data and specific workloads where...
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Distributed adaptive nearest neighbor classifier: algorithm and theory
When data is of an extraordinarily large size or physically stored in different locations, the distributed nearest neighbor (NN) classifier is an...
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Imbalanced instance selection based on Laplacian matrix decomposition with weighted k-nearest-neighbor graph
Data are an essential component for building machine learning models. Linearly separable high-quality data are conducive to building efficient...
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K-Nearest Neighbor
This chapter first describes the k-NN algorithm, then discusses the model and three basic elements of k-NN, and finally describes an implementation...
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Fast spectral analysis for approximate nearest neighbor search
In large-scale machine learning, of central interest is the problem of approximate nearest neighbor (ANN) search, where the goal is to query...
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Indexing dynamic encrypted database in cloud for efficient secure k-nearest neighbor query
Secure k -Nearest Neighbor ( k -NN) query aims to find k nearest data of a given query from an encrypted database in a cloud server without revealing...
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A water quality prediction method based on k-nearest-neighbor probability rough sets and PSO-LSTM
Water security has attracted a lot of attention in the world, and water quality assessment is the main task to ensure water security. In China, as an...
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Adaptive Discriminant and Quasiconformal Kernel Nearest Neighbor Classification
Nearest neighbor classification assumes locally constant class conditional probabilities. This assumption becomes invalid in high dimensions due to...
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Continuous Group Nearest Neighbor Query over Sliding Window
Group nearest neighbor query(GNN for short) is a classic problem in the spatial database field. Given a data point set D, a query point set Q, the...