:We formulate structure from motion as a Bayesian inference problem, and use a Markov chain Monte Carlo sampler to sample the posterior on this problem. This results in a method th...
In this paper we present a centralized flow control scheme in NoCs in the presence of both elastic and streaming flow traffic paradigms. We model the desired Best Effort (BE) sour...
We present an efficient generalization of the sparse pseudo-input Gaussian process (SPGP) model developed by Snelson and Ghahramani [1], applying it to binary classification pro...
The control of high-dimensional, continuous, non-linear dynamical systems is a key problem in reinforcement learning and control. Local, trajectory-based methods, using techniques...
This paper deals with clustering of spatially distributed data using wireless sensor networks. A distributed low-complexity clustering algorithm is developed that requires one-hop...
Pedro A. Forero, Alfonso Cano, Georgios B. Giannak...