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ICML
1995
IEEE
16 years 4 months ago
Visualizing High-Dimensional Structure with the Incremental Grid Growing Neural Network
Understanding high-dimensional real world data usually requires learning the structure of the data space. The structure maycontain high-dimensional clusters that are related in co...
Justine Blackmore, Risto Miikkulainen
APPML
2002
58views more  APPML 2002»
15 years 3 months ago
Layered clusters of tightness set functions
A method for structural clustering is proposed involving data on subset-to-entity linkages that can be calculated with structural data such as graphs or sequences or images. The m...
Boris Mirkin, Ilya B. Muchnik
APPROX
2009
Springer
107views Algorithms» more  APPROX 2009»
15 years 10 months ago
Hierarchy Theorems for Property Testing
Referring to the query complexity of property testing, we prove the existence of a rich hierarchy of corresponding complexity classes. That is, for any relevant function q, we prov...
Oded Goldreich, Michael Krivelevich, Ilan Newman, ...
ISMIS
2009
Springer
15 years 10 months ago
Novelty Detection from Evolving Complex Data Streams with Time Windows
Abstract. Novelty detection in data stream mining denotes the identification of new or unknown situations in a stream of data elements flowing continuously in at rapid rate. This...
Michelangelo Ceci, Annalisa Appice, Corrado Loglis...
INFOVIS
2000
IEEE
15 years 8 months ago
Density Functions for Visual Attributes and Effective Partitioning in Graph Visualization
Two tasks in Graph Visualization require partitioning: the assignment of visual attributes and divisive clustering. Often, we would like to assign a color or other visual attribut...
Ivan Herman, M. Scott Marshall, Guy Melanço...