This brief presents an efficient and scalable online learning algorithm for recurrent neural networks (RNNs). The approach is based on the real-time recurrent learning (RTRL) algor...
The financial services industry today produces and consumes huge amounts of data and the processes involved in analysing these data are equally huge especially in terms of their c...
Rafael Moreno-Vozmediano, Krishna Nadiminti, Sriku...
We present a novel approach for efficient path planning and navigation of multiple virtual agents in complex dynamic scenes. We introduce a new data structure, Multiagent Navigatio...
Avneesh Sud, Erik Andersen, Sean Curtis, Ming C. L...
It is difficult to render caustic patterns at interactive frame rates. This paper introduces new rendering techniques that relax current constraints, allowing scenes with moving, n...
We present a technique for accelerating the rendering of high depth-complexity scenes. In a preprocessing stage, we approximate the input model with a hierarchical data structure ...
Fausto Bernardini, James T. Klosowski, Jihad El-Sa...