When we learn a new motor skill, we have to contend with both the variability inherent in our sensors and the task. The sensory uncertainty can be reduced by using information abo...
Variability of process parameters makes prediction of digital circuit timing characteristics an important and challenging problem in modern chip design. Recently, statistical stat...
Hongliang Chang, Vladimir Zolotov, Sambasivan Nara...
This paper considers humming-based human verification and identification systems. Humming of a target person is modeled as a Gaussian mixture model, and the matching score betwe...
Stochastic relational models (SRMs) [15] provide a rich family of choices for learning and predicting dyadic data between two sets of entities. The models generalize matrix factor...
Abstract— Artificial neural networks have proved an attractive approach to non-linear regression problems arising in environmental modelling, such as statistical downscaling, sh...
Gavin C. Cawley, Malcolm R. Haylock, Stephen R. Do...