The question raised in [15] is answered how to naturally dely used forms of recursion by abstract machines. We show that turbo ASMs as defined in [7] allow one to faithfully refl...
We combine three threads of research on approximate dynamic programming: sparse random sampling of states, value function and policy approximation using local models, and using lo...
As probabilistic computations play an increasing role in solving various problems, researchers have designed probabilistic languages that treat probability distributions as primit...
In previous work we have developed and prototyped a silicon compiler which translates a functional language (SAFL) into hardware. Here we present a SAFL-level program transformati...
This paper proposes a new randomized strategy for adaptive MCMC using Bayesian optimization. This approach applies to nondifferentiable objective functions and trades off explor...