“The curse of dimensionality” is pertinent to many learning algorithms, and it denotes the drastic raise of computational complexity and classification error in high dimension...
Mykola Pechenizkiy, Seppo Puuronen, Alexey Tsymbal
We develop and evaluate an approach to causal modeling based on time series data, collectively referred to as“grouped graphical Granger modeling methods.” Graphical Granger mo...
Aurelie C. Lozano, Naoki Abe, Yan Liu, Saharon Ros...
Classification is an important data mining problem. Given a training database of records, each tagged with a class label, the goal of classification is to build a concise model ...
Johannes Gehrke, Venkatesh Ganti, Raghu Ramakrishn...
Many applications require the management of spatial data. Clustering large spatial databases is an important problem which tries to find the densely populated regions in the featu...
Multidimensional discrete data (MDD), i.e., arrays of arbitrary size, dimension, and base type, are receiving growing attention among the database community. MDD occur in a variet...
Peter Baumann, Paula Furtado, Roland Ritsch, Norbe...