Reinforcement learning algorithms can become unstable when combined with linear function approximation. Algorithms that minimize the mean-square Bellman error are guaranteed to co...
— In this paper, we address the problem of FSM state assignment to minimize area and power. The objectives are targeted as single/independent as well as multi-objective optimizat...
We study the convergence properties of an alternating proximal minimization algorithm for nonconvex structured functions of the type: L(x, y) = f(x)+Q(x, y)+g(y), where f : Rn → ...
— In large-scale fingerprinting localization systems, fine-grained location estimation and quick location determination are conflicting concerns. To achieve finer-grained loc...
Buffer insertion is an effective approach to achieve both minimal clock signal delay and skew in high speed VLSI circuit design. In this paper, we develop an optimal buffer ins...