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Shared Nearest Neighbor Calibration for Few-Shot Classification
Few-shot classification aims to classify query samples using very few labeled examples. Most existing methods follow the Prototypical Network to...
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Solving TSP by using combinatorial Bees algorithm with nearest neighbor method
Bees Algorithm (BA) is a popular meta-heuristic method that has been used in many different optimization areas for years. In this study, a new...
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Efficient exact k-flexible aggregate nearest neighbor search in road networks using the M-tree
This study proposes an efficient exact k -flexible aggregate nearest neighbor ( k -FANN) search algorithm in road networks using the M-tree. The...
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Adaptive active learning through k-nearest neighbor optimized local density clustering
Active learning iteratively constructs a refined training set to train an effective classifier with as few labeled instances as possible. In areas...
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Delaunay walk for fast nearest neighbor: accelerating correspondence matching for ICP
Point set registration algorithms such as Iterative Closest Point (ICP) are commonly utilized in time-constrained environments like robotics. Finding...
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A practical privacy-preserving nearest neighbor searching method over encrypted spatial data
To realize the great flexibility and cost savings for providing location-based service, data owners are incentivized to migrate their data to cloud...
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Nearest Neighbor Algorithms
Most of the practical data sets are high-dimensional. A major difficulty with classifying such data is involved not only in terms of the...
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A meta-indexing method for fast probably approximately correct nearest neighbor searches
In this paper we present an indexing method for probably approximately correct nearest neighbor queries in high dimensional spaces capable of...
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A scalable solution to the nearest neighbor search problem through local-search methods on neighbor graphs
Nearest neighbor search is a powerful abstraction for data access; however, data indexing is troublesome even for approximate indexes. For...
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K-Nearest Neighbor
Most machine learning applications have at least two stages: the learning stage and the deployment stage. K-nn is a lazy learner, that is, unlike the...
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Residual Vector Product Quantization for Approximate Nearest Neighbor Search
Product Quantization is popular for approximate nearest neighbor search, which decomposes the vector space into Cartesian product of several...
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Optimization Strategies for the k-Nearest Neighbor Classifier
In this paper, we propose six (6) fast and efficient classification schemes for different type of images (digits, objects, characters) using the...
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Nearest-Neighbor Methods: A Modern Perspective
This chapter aims at providing an overview of various modern approaches to learning with nearest neighbors in general metric spaces. We provide the...
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Approximate k-Nearest Neighbor Query over Spatial Data Federation
Approximate nearest neighbor query is a fundamental spatial query widely applied in many real-world applications. In the big data era, there is an...
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Connecting Compression Spaces with Transformer for Approximate Nearest Neighbor Search
We propose a generic feature compression method for Approximate Nearest Neighbor Search (ANNS) problems, which speeds up existing ANNS methods in a...
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GPU-Based Algorithms for Processing the k Nearest-Neighbor Query on Spatial Data Using Partitioning and Concurrent Kernel Execution
Algorithms for answering the k nearest-neighbor ( k -NN) query are widely used for queries in spatial databases and for distance classification of a...
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Cross-View Nearest Neighbor Contrastive Learning of Human Skeleton Representation
Traditional self-supervised contrastive learning approaches regard different views of the same skeleton sequence as a positive pair for the...
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Continuous Group Nearest Group Search over Streaming Data
Group nearest group query(GNG for short) is an important variant of NN search. Let...
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A dynamic density-based clustering method based on K-nearest neighbor
Many density-based clustering algorithms already proposed in the literature are capable of finding clusters with different shapes, sizes, and...
