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In this paper, we propose a method to detect abnormal events using a novel unsupervised kernel learning algorithm. The key of our method is to learn a suitable feature space and the associated kernel function of the training samples. By considering the self-similarity property of training samples, we assume that the training samples will show the distinctly(More)
The key in agglomerative clustering is to define the affinity measure between two sets. A novel agglomerative clustering method is proposed by utilizing the path integral to define the affinity measure. Firstly, the path integral descriptor of an edge, a node and a set is computed by path integral and exponent generating function. Then, the affinity measure(More)
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