Learning temporal causal graph structures from multivariate time-series data reveals important dependency relationships between current observations and histories, and provides a ...
Yan Liu 0002, Alexandru Niculescu-Mizil, Aurelie C...
Background: The usefulness of log2 transformation for cDNA microarray data has led to its widespread application to Affymetrix data. For Affymetrix data, where absolute intensitie...
Kellie J. Archer, Catherine I. Dumur, Viswanathan ...
Latent variable models represent the probability density of data in a space of several dimensions in terms of a smaller number of latent, or hidden, variables. A familiar example ...
Active power used to be the primary contributor to total power dissipation of CMOS designs, but with the technology scaling, the share of leakage in total power consumption of dig...
Hamid Noori, Maziar Goudarzi, Koji Inoue, Kazuaki ...
Access to distributed databases containing tuples collected about mobile physical objects requires information about the objects’ trajectories. Existing access control models ca...