Research in reinforcement learning has produced algorithms for optimal decision making under uncertainty that fall within two main types. The first employs a Bayesian framework, ...
Many computation-intensive or recursive applications commonly found in digital signal processing and image processing applications can be represented by data-flow graphs (DFGs). ...
This paper presents a novel and fast image-space collision detection algorithm with the A-buffer, where the GPU computes the potentially colliding sets (PCSs), and the CPU performs...
We consider online problems where purchases have time durations which expire regardless of whether the purchase is used or not. The Parking Permit Problem is the natural analog of...
We show that the problem of computing a minimum distortion embedding of a given graph into a path remains NP-hard when the input graph is restricted to a bipartite, cobipartite, o...