We address two open theoretical questions in Policy Gradient Reinforcement Learning. The first concerns the efficacy of using function approximation to represent the state action ...
This paper describes a new approach to neural network implementation of photometric stereo for a rotational object with non-uniform reflectance factor. Three input images are acqu...
Yuji Iwahori, Yumi Watanabe, Robert J. Woodham, Ak...
Neural spike trains present challenges to analytical efforts due to their noisy, spiking nature. Many studies of neuroscientific and neural prosthetic importance rely on a smooth...
John P. Cunningham, Byron M. Yu, Krishna V. Shenoy...
The Gaussian approximation is known to be quite accurate for estimating the system performance of an optically pre–amplified on-off keying (OOK) system in the presence of multipl...
It is known that the frame error rate of turbo codes on quasi-static fading channels can be accurately approximated using the convergence threshold of the corresponding iterative d...
Ioannis Chatzigeorgiou, Ian J. Wassell, Rolando A....