Fast PNN-based Clustering Using K-nearest Neighbor Graph
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
An efficient law-of-cosine-based search for vector quantization
Pattern Recognition Letters
Fast Agglomerative Clustering Using a k-Nearest Neighbor Graph
IEEE Transactions on Pattern Analysis and Machine Intelligence
Faster and more robust point symmetry-based K-means algorithm
Pattern Recognition
Iterative shrinking method for clustering problems
Pattern Recognition
A fast VQ codebook generation algorithm using codeword displacement
Pattern Recognition
A novel approach for fast codebook re-quantization
Pattern Recognition
Improvement of the k-means clustering filtering algorithm
Pattern Recognition
Fast codebook search algorithm for vector quantization using sorting technique
Proceedings of the International Conference on Advances in Computing, Communication and Control
A fast VQ codebook generation algorithm via pattern reduction
Pattern Recognition Letters
A new integer image coding technique based on orthogonal polynomials
Image and Vision Computing
A fast k-means clustering algorithm using cluster center displacement
Pattern Recognition
On the efficiency of swap-based clustering
ICANNGA'09 Proceedings of the 9th international conference on Adaptive and natural computing algorithms
Evolutionary clustering based vector quantization and SPIHT coding for image compression
Pattern Recognition Letters
An agglomerative clustering algorithm using a dynamic k-nearest-neighbor list
Information Sciences: an International Journal
Comparison of clustering methods: A case study of text-independent speaker modeling
Pattern Recognition Letters
Continuous space pattern reduction for genetic clustering algorithm
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
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This paper introduces a new method for reducing the number of distance calculations in the generalized Lloyd algorithm (GLA), which is a widely used method to construct a codebook in vector quantization. Reduced comparison search detects the activity of the code vectors and utilizes it on the classification of the training vectors. For training vectors whose current code vector has not been modified, we calculate distances only to the active code vectors. A large proportion of the distance calculations can be omitted without sacrificing the optimality of the partition. The new method is included in several fast GLA variants reducing their running times over 50% on average