We address the problem of learning structure in nonlinear Markov networks with continuous variables. This can be viewed as non-Gaussian multidimensional density estimation exploit...
The multidimensional, heterogeneous, and temporal nature of speech databases raises interesting challenges for representation and query. Recently, annotation graphs have been prop...
The discovery of subsets with special properties from binary data has been one of the key themes in pattern discovery. Pattern classes such as frequent itemsets stress the co-occu...
Eino Hinkkanen, Hannes Heikinheimo, Heikki Mannila...
Background: The integration of biomedical information is essential for tackling medical problems. We describe a data model in the domain of flow cytometry (FC) allowing for massiv...
John Drakos, Marina Karakantza, Nicholas C. Zoumbo...
We present learning and inference algorithms for a versatile class of partially observed vector autoregressive (VAR) models for multivariate time-series data. VAR models can captu...