This paper analyses the Contrastive Divergence algorithm for learning statistical parameters. We relate the algorithm to the stochastic approximation literature. This enables us t...
This paper presents a general method to derive tight rates of convergence for numerical approximations in optimal control when we consider variable resolution grids. We study the ...
— We consider the issue of fair share of the spectrum opportunity for the case of spectrum-overlay cognitive radio networks. Owing to the decentralized nature of the network, we ...
Abstract— The paper deals with estimating transfer functions of stable linear time-invariant systems under stochastic assumptions. We adopt a nonparametric minimax approach for m...
The normalized number of key comparisons needed to sort a list of randomly permuted items by the Quicksort algorithm is known to converge in distribution. We identify the rate of ...