Approximate Bayesian Gaussian process (GP) classification techniques are powerful nonparametric learning methods, similar in appearance and performance to support vector machines....
Approximations based on dyadic centred intervals are investigated as a means for implementing exact real arithmetic. It is shown that the field operations can be implemented on th...
Abstract— In this paper, we consider a class of continuoustime, continuous-space stochastic optimal control problems. Building upon recent advances in Markov chain approximation ...
: We adapt a combinatorial optimization algorithm, extremal optimization (EO), for the search problem in computational protein design. This algorithm takes advantage of the knowled...
Abstract. Improving image quality is the backbone of highly competitive display industry. Contemporary video processing system design is a challenging optimization problem. General...