Abstract. To improve the efficiency of the currently known evolutionary algorithms, we have proposed two complementary efficiency speed-up strategies in our previous research work ...
Abstract. It is customary to write performance-critical parts of arithmetic functions in assembly: this enables finely-tuned algorithms that use specialized processor instructions....
We study a sequential variance reduction technique for Monte Carlo estimation of functionals in Markov Chains. The method is based on designing sequential control variates using s...
We construct simple algorithms for high-dimensional numerical integration of function classes with moderate smoothness. These classes consist of square-integrable functions over t...
The reward functions that drive reinforcement learning systems are generally derived directly from the descriptions of the problems that the systems are being used to solve. In so...