This paper deals with generalized procrustes analysis. This is the problem of registering a set of shape data by finding a reference shape and global rigid transformations given p...
Stochastic gradient descent (SGD) uses approximate gradients estimated from subsets of the training data and updates the parameters in an online fashion. This learning framework i...
Recently, a number of researchers have proposed spectral algorithms for learning models of dynamical systems—for example, Hidden Markov Models (HMMs), Partially Observable Marko...
This paper proposes a traffic model and a parameter fitting procedure that are capable of achieving accurate prediction of the queuing behavior for IP traffic exhibiting long-rang...
— The aggregate power consumption of the Internet is increasing at an alarming rate, due in part to the rapid increase in the number of connected edge devices such as desktop PCs...