We present a technique for optimizing the rendering of highdepth complexity scenes. Prioritized-Layered Projection (PLP) does this by rendering an estimation of the visible set fo...
To avoid the curse of dimensionality, function approximators are used in reinforcement learning to learn value functions for individual states. In order to make better use of comp...
This paper studies the problem of e ciently scheduling fully strict (i.e., wellstructured) multithreaded computations on parallel computers. A popular and practical method of sche...
Abstract-- We describe new graph bipartization algorithms for layout modification and phase assignment of bright-field alternating phaseshifting masks (AltPSM) [25]. The problem of...
Andrew B. Kahng, Shailesh Vaya, Alexander Zelikovs...
This paper summarizes research on a new emerging framework for learning to plan using the Markov decision process model (MDP). In this paradigm, two approaches to learning to plan...
Sridhar Mahadevan, Sarah Osentoski, Jeffrey Johns,...