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Efficient kNN Algorithm Based on Graph Sparse ...
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由 S Zhang 著作2014被引用 51 次 — This paper proposes an efficient k Nearest Neighbors (kNN) method based on a graph sparse reconstruction framework, called Graph Sparse kNN (GS-kNN for ...
Efficient kNN Algorithm Based on Graph Sparse ...
Springer
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由 S Zhang 著作2014被引用 51 次 — Abstract. This paper proposes an efficient k Nearest Neighbors (kNN) method based on a graph sparse reconstruction framework, called Graph Sparse kNN.
14 頁
Efficient kNN Algorithm Based on Graph Sparse ...
ResearchGate
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2024年11月21日 — This paper proposes an efficient k Nearest Neighbors (kNN) method based on a graph sparse reconstruction framework, called Graph Sparse kNN ...
(PDF) Efficient kNN Classification With Different Numbers ...
ResearchGate
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ResearchGate
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2019年12月5日 — This paper proposes a kTree method to learn different optimal k values for different test/new samples, by involving a training stage in the kNN classification.
Efficient kNN Classification With Different Numbers of ...
IEEE Xplore
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IEEE Xplore
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由 S Zhang 著作2017被引用 1321 次 — The kNN based on graph sparse reconstruction (GS-kNN) method in [30] ... Cheng, “Efficient kNN algorithm based on graph sparse reconstruction,” in Proc.
12 頁
Style linear k-nearest neighbor classification method
ScienceDirect.com
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ScienceDirect.com
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由 J Zhang 著作2024被引用 1 次 — In order to obtain easy implementation of the proposed Style-KNN method, an alternating optimization strategy is adopted to optimize its objective function.
The case of KNN graph construction
Inria
https://lirima.inria.fr › files › 2020/03 › AnneMa...
Inria
https://lirima.inria.fr › files › 2020/03 › AnneMa...
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由 A Boutet 著作被引用 31 次 — We motivate and present KIFF, a scalable, efficient, and accurate algorithm to compute approximate KNN graphs. KIFF is designed for datasets in which nodes are ...
12 頁
Debo Cheng
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Efficient kNN algorithm based on graph sparse reconstruction. S Zhang, M Zong, K Sun, Y Liu, D Cheng. Advanced Data Mining and Applications: 10th International ...
Learning k for kNN Classification - ACM Digital Library
ACM Digital Library
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由 S Zhang 著作2017被引用 858 次 — This article proposes to learn a correlation matrix to reconstruct test data points by training data to assign different k values to different test data points.
Efficient K-Nearest Neighbor Graph Construction for Generic ...
Princeton University
https://www.cs.princeton.edu › papers › www11
Princeton University
https://www.cs.princeton.edu › papers › www11
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由 W Dong 著作被引用 839 次 — We present NN-Descent, a simple yet efficient algorithm for approximate K-NNG con- struction with arbitrary similarity measures. Our method is.
10 頁