Since the seminal work of Stein in the 1950s, there has been continuing research devoted to improving the total meansquared error (MSE) of the least-squares (LS) estimator in the l...
When constructing a classifier, the probability of correct classification of future data points should be maximized. We consider a binary classification problem where the mean and...
Gert R. G. Lanckriet, Laurent El Ghaoui, Chiranjib...
In modern circuit design, it is difficult to provide reliable parametric yield prediction since the real distribution of process data is hard to measure. Most existing approaches ...
We consider a two-dimensional problem of positron emission tomography where the random mechanism of the generation of the tomographic data is modeled by Poisson processes. The goa...
The adaptive estimation of a time-varying parameter vector in a linear Gaussian model is considered where we a priori know that the parameter vector belongs to a known arbitrary s...