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» Approximation schemes for clustering problems
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ESANN
2006
15 years 6 months ago
Data topology visualization for the Self-Organizing Map
The Self-Organizing map (SOM), a powerful method for data mining and cluster extraction, is very useful for processing data of high dimensionality and complexity. Visualization met...
Kadim Tasdemir, Erzsébet Merényi
FOCS
2009
IEEE
16 years 5 days ago
Settling the Complexity of Arrow-Debreu Equilibria in Markets with Additively Separable Utilities
We prove that the problem of computing an Arrow-Debreu market equilibrium is PPAD-complete even when all traders use additively separable, piecewise-linear and concave utility fun...
Xi Chen, Decheng Dai, Ye Du, Shang-Hua Teng
EDBT
2004
ACM
142views Database» more  EDBT 2004»
16 years 5 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...
ISPAN
2005
IEEE
15 years 11 months ago
A Scalable Method for Predicting Network Performance in Heterogeneous Clusters
An important requirement for the effective scheduling of parallel applications on large heterogeneous clusters is a current view of system resource availability. Maintaining such ...
Dimitrios Katramatos, Steve J. Chapin
AAAI
2007
15 years 7 months ago
COD: Online Temporal Clustering for Outbreak Detection
We present Cluster Onset Detection (COD), a novel algorithm to aid in detection of epidemic outbreaks. COD employs unsupervised learning techniques in an online setting to partiti...
Tomás Singliar, Denver Dash