Fractal functions are explored as a representation for rough data in computer graphics. Two new techniques for using fractal interpolation functions to approximate rough functions...
A heuristic method to construct uniform approximations to analytic transcendental functions is developed as a generalization of the Hermite-Pad´e interpolation to infinite interv...
Functional dependencies (FDs) are an integral part of database theory since they are used in integrity enforcement and in database design. Recently, functional dependencies satis...
We address two open theoretical questions in Policy Gradient Reinforcement Learning. The first concerns the efficacy of using function approximation to represent the state action ...
Reinforcement learning problems are commonly tackled with temporal difference methods, which attempt to estimate the agent's optimal value function. In most real-world proble...