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WCE
2007
8 years 4 months ago
Surface Classification from Aircraft Icing Droplet Splash Images
— The build up of water ice on aircraft flight surfaces poses a significant safety risk. As a result, much effort has gone into studying this problem in order to understand how i...
Xueqing Zhang, Stuart Barnes, David W. Hammond
NIPS
1994
8 years 4 months ago
Convergence Properties of the K-Means Algorithms
This paper studies the convergence properties of the well known K-Means clustering algorithm. The K-Means algorithm can be described either as a gradient descent algorithmor by sl...
Léon Bottou, Yoshua Bengio
DMIN
2006
122views Data Mining» more  DMIN 2006»
8 years 4 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...
ATAL
2003
Springer
8 years 8 months ago
A method for decentralized clustering in large multi-agent systems
This paper examines a method of clustering within a fully decentralized multi-agent system. Our goal is to group agents with similar objectives or data, as is done in traditional ...
Elth Ogston, Benno J. Overeinder, Maarten van Stee...
BVAI
2005
Springer
8 years 8 months ago
Algorithm That Mimics Human Perceptual Grouping of Dot Patterns
We propose an algorithm that groups points similarly to how human observers do. It is simple, totally unsupervised and able to find clusters of complex and not necessarily convex s...
Giuseppe Papari, Nicolai Petkov
ESORICS
2005
Springer
8 years 8 months ago
Privacy Preserving Clustering
The freedom and transparency of information flow on the Internet has heightened concerns of privacy. Given a set of data items, clustering algorithms group similar items together...
Somesh Jha, Louis Kruger, Patrick McDaniel
COMPGEOM
2006
ACM
8 years 9 months ago
A fast k-means implementation using coresets
In this paper we develop an efficient implementation for a k-means clustering algorithm. The novel feature of our algorithm is that it uses coresets to speed up the algorithm. A ...
Gereon Frahling, Christian Sohler
MLDM
2007
Springer
8 years 9 months ago
Kernel MDL to Determine the Number of Clusters
In this paper we propose a new criterion, based on Minimum Description Length (MDL), to estimate an optimal number of clusters. This criterion, called Kernel MDL (KMDL), is particu...
Ivan O. Kyrgyzov, Olexiy O. Kyrgyzov, Henri Ma&ici...
CEC
2008
IEEE
8 years 9 months ago
A Quantum-inspired Genetic Algorithm for data clustering
—The conventional K-Means clustering algorithm must know the number of clusters in advance and the clustering result is sensitive to the selection of the initial cluster centroid...
Jing Xiao, YuPing Yan, Ying Lin, Ling Yuan, Jun Zh...
ICDM
2009
IEEE
133views Data Mining» more  ICDM 2009»
8 years 10 months ago
On K-Means Cluster Preservation Using Quantization Schemes
This work examines under what conditions compression methodologies can retain the outcome of clustering operations. We focus on the popular k-Means clustering algorithm and we dem...
Deepak S. Turaga, Michail Vlachos, Olivier Versche...
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