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» Discriminative K-means for Clustering
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MMM
2012
Springer
294views Multimedia» more  MMM 2012»
12 years 3 months ago
Improving Cluster Selection and Event Modeling in Unsupervised Mining for Automatic Audiovisual Video Structuring
Abstract. Can we discover audio-visually consistent events from videos in a totally unsupervised manner? And, how to mine videos with different genres? In this paper we present our...
Anh-Phuong Ta, Mathieu Ben, Guillaume Gravier
CVPR
2012
IEEE
11 years 10 months ago
Non-negative low rank and sparse graph for semi-supervised learning
Constructing a good graph to represent data structures is critical for many important machine learning tasks such as clustering and classification. This paper proposes a novel no...
Liansheng Zhuang, Haoyuan Gao, Zhouchen Lin, Yi Ma...
EDBT
2004
ACM
142views Database» more  EDBT 2004»
14 years 7 months ago
Iterative Incremental Clustering of Time Series
We present a novel anytime version of partitional clustering algorithm, such as k-Means and EM, for time series. The algorithm works by leveraging off the multi-resolution property...
Jessica Lin, Michail Vlachos, Eamonn J. Keogh, Dim...
DMIN
2006
122views Data Mining» more  DMIN 2006»
13 years 9 months ago
Clustering of Bi-Dimensional and Heterogeneous Time Series: Application to Social Sciences Data
We present an application of bi-dimensional and heterogeneous time series clustering in order to resolve a Social Sciences issue. The dataset is the result of a survey involving mo...
Rémi Gaudin, Sylvaine Barbier, Nicolas Nico...
ERCIMDL
2000
Springer
147views Education» more  ERCIMDL 2000»
13 years 11 months ago
Map Segmentation by Colour Cube Genetic K-Mean Clustering
Segmentation of a colour image composed of different kinds of texture regions can be a hard problem, namely to compute for an exact texture fields and a decision of the optimum num...
Vitorino Ramos, Fernando Muge