This paper presents a new method called Transition-based RRT (T-RRT) for path planning problems in continuous cost spaces. It combines the exploration strength of the RRT algorith...
In kernel-based regression learning, optimizing each kernel individually is useful when the data density, curvature of regression surfaces (or decision boundaries) or magnitude of...
Abstract. During development, processor architectures can be tuned and configured by many different parameters. For benchmarking, automatic design space explorations (DSEs) with h...
Ralf Jahr, Horia Calborean, Lucian Vintan, Theo Un...
In this paper we introduce the concept and method for adaptively tuning the model complexity in an online manner as more examples become available. Challenging classification pro...