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NIPS
2001
13 years 9 months ago
Rates of Convergence of Performance Gradient Estimates Using Function Approximation and Bias in Reinforcement Learning
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 ...
Gregory Z. Grudic, Lyle H. Ungar
ICPR
2002
IEEE
14 years 9 months ago
Self-Calibration and Neural Network Implementation of Photometric Stereo
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...
NIPS
2007
13 years 10 months ago
Inferring Neural Firing Rates from Spike Trains Using Gaussian Processes
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...
ICC
2007
IEEE
14 years 2 months ago
On the Accuracy of the Gaussian Approximation for Performance Estimation in Optical DPSK Systems with In-Band Crosstalk
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...
Luís G. C. Cancela, João J. O. Pires
CISS
2008
IEEE
13 years 10 months ago
On the frame error rate of transmission schemes on quasi-static fading channels
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....