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TNN
2010
176views Management» more  TNN 2010»
13 years 2 months ago
On the weight convergence of Elman networks
Abstract--An Elman network (EN) can be viewed as a feedforward (FF) neural network with an additional set of inputs from the context layer (feedback from the hidden layer). Therefo...
Qing Song
AAAI
2006
13 years 9 months ago
Action Selection in Bayesian Reinforcement Learning
My research attempts to address on-line action selection in reinforcement learning from a Bayesian perspective. The idea is to develop more effective action selection techniques b...
Tao Wang
CVPR
2011
IEEE
13 years 4 months ago
Shape Grammar Parsing via Reinforcement Learning
This paper tackles shape grammar parsing for facade segmentation using a novel optimization approach based on reinforcement learning (RL). To this end, we use a binary recursive g...
Olivier Teboul, Iasonas Kokkinos, Panagiotis Kouts...
UAI
2003
13 years 9 months ago
On the Convergence of Bound Optimization Algorithms
Many practitioners who use EM and related algorithms complain that they are sometimes slow. When does this happen, and what can be done about it? In this paper, we study the gener...
Ruslan Salakhutdinov, Sam T. Roweis, Zoubin Ghahra...
EUROCAST
2007
Springer
182views Hardware» more  EUROCAST 2007»
14 years 1 months ago
A k-NN Based Perception Scheme for Reinforcement Learning
Abstract a paradigm of modern Machine Learning (ML) which uses rewards and punishments to guide the learning process. One of the central ideas of RL is learning by “direct-online...
José Antonio Martin H., Javier de Lope Asia...