Standard pattern discovery techniques, such as association rules, suffer an extreme risk of finding very large numbers of spurious patterns for many knowledge discovery tasks. The...
Pattern discovery techniques, such as association rule discovery, explore large search spaces of potential patterns to find those that satisfy some user-specified constraints. Due...
We generalize Shimizu et al's (2006) ICA-based approach for discovering linear non-Gaussian acyclic (LiNGAM) Structural Equation Models (SEMs) from causally sufficient, conti...
Gustavo Lacerda, Peter Spirtes, Joseph Ramsey, Pat...
Time series pattern mining (TSPM) finds correlations or dependencies in same series or in multiple time series. When the numerous instances of multiple time series data are associ...
Discovering hidden patterns in large sets of workforce schedules to gain insight into the potential knowledge in workforce schedules are crucial to better understanding the workfor...