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» Approximation schemes for clustering problems
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ANNPR
2008
Springer
15 years 5 months ago
Patch Relational Neural Gas - Clustering of Huge Dissimilarity Datasets
Clustering constitutes an ubiquitous problem when dealing with huge data sets for data compression, visualization, or preprocessing. Prototype-based neural methods such as neural g...
Alexander Hasenfuss, Barbara Hammer, Fabrice Rossi
149
Voted
NIPS
2008
15 years 4 months ago
Regularized Co-Clustering with Dual Supervision
By attempting to simultaneously partition both the rows (examples) and columns (features) of a data matrix, Co-clustering algorithms often demonstrate surprisingly impressive perf...
Vikas Sindhwani, Jianying Hu, Aleksandra Mojsilovi...
NIPS
2007
15 years 4 months ago
Consistent Minimization of Clustering Objective Functions
Clustering is often formulated as a discrete optimization problem. The objective is to find, among all partitions of the data set, the best one according to some quality measure....
Ulrike von Luxburg, Sébastien Bubeck, Stefa...
130
Voted
DKE
2006
125views more  DKE 2006»
15 years 3 months ago
Online clustering of parallel data streams
In recent years, the management and processing of so-called data streams has become a topic of active research in several fields of computer science such as, e.g., distributed sys...
Jürgen Beringer, Eyke Hüllermeier
136
Voted
IEEECIT
2009
IEEE
15 years 10 months ago
Clustering of Software Systems Using New Hybrid Algorithms
—Software clustering is a method for increasing software system understanding and maintenance. Software designers, first use MDG graph to model the structure of software system. ...
Ali Safari Mamaghani, Mohammad Reza Meybodi