In this paper we propose a new nonparametric approach to identification of linear time invariant systems using subspace methods. The nonparametric paradigm to prediction of station...
Alessandro Chiuso, Gianluigi Pillonetto, Giuseppe ...
Abstract Barrier synchronizations can be very expensive on multiprogramming environment because no process can go past a barrier until all the processes have arrived. If a process ...
Title of thesis: EFFICIENT AND ACCURATE STATISTICAL TIMING ANALYSIS FOR NON-LINEAR NON-GAUSSIAN VARIABILITY WITH INCREMENTAL ATTRIBUTES Ashish Dobhal, Master of Science, 2006 Thes...
We give a fast and practical algorithm for statistical learning hyperparameters from observable data in probabilistic image processing, which is based on Gaussian graphical model ...
This paper develops a Bayesian network (BN) predictor to profile cross-race gene expression data. Cross-race studies face more data variability than single-lab studies. Our desig...