Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/71676
Title: Robust graph mode seeking by graph shift
Authors: Liu, H. 
Yan, S. 
Issue Date: 2010
Source: Liu, H.,Yan, S. (2010). Robust graph mode seeking by graph shift. ICML 2010 - Proceedings, 27th International Conference on Machine Learning : 671-678. ScholarBank@NUS Repository.
Abstract: In this paper, we study how to robustly compute the modes of a graph, namely the dense subgraphs, which characterize the underlying compact patterns and are thus useful for many applications. We first define the modes based on graph density function, then propose the graph shift algorithm, which starts from each vertex and iteratively shifts towards the nearest mode of the graph along a certain trajectory. Both theoretic analysis and experiments show that graph shift algorithm is very efficient and robust, especially when there exist large amount of noises and outliers. Copyright 2010 by the author(s)/owner(s).
Source Title: ICML 2010 - Proceedings, 27th International Conference on Machine Learning
URI: http://scholarbank.nus.edu.sg/handle/10635/71676
ISBN: 9781605589077
Appears in Collections:Staff Publications

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