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...
We propose a new wavelet compression algorithm based on the rate-distortion optimization for densely sampled triangular meshes. Exploiting the normal remesher of Guskov et al., th...
Abstract-- Computing constrained shortest paths is fundamental to some important network functions such as QoS routing, which is to find the cheapest path that satisfies certain co...
The Internet has instigated a critical need for automated tools that facilitate integrating countless databases. Since non-technical end users are often the ultimate repositories ...
In this paper, we address the problem of determining the 2D relative pose of pairs of communicating robots from (i) robot-to-robot distance measurements and (ii) displacement estim...