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» Modeling Neural Processes in Lindenmayer Systems
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GECCO
2009
Springer
109views Optimization» more  GECCO 2009»
15 years 2 months ago
A genetic algorithm for learning significant phrase patterns in radiology reports
Radiologists disagree with each other over the characteristics and features of what constitutes a normal mammogram and the terminology to use in the associated radiology report. R...
Robert M. Patton, Thomas E. Potok, Barbara G. Beck...
ICASSP
2009
IEEE
15 years 4 months ago
A new stochastic estimator for tremor frequency tracking
An important parameter in analysis of physiological tremor is the diagnosis and study of neurological disorders. The instantaneous tremor frequency (ITF) is an important parameter...
Alp Kucukelbir, Azadeh Kushki, Konstantinos N. Pla...
CDC
2009
IEEE
108views Control Systems» more  CDC 2009»
15 years 2 months ago
The parabigeminal nucleus as a recursive estimator
— The parabigeminal nucleus (PBN) is known to estimate the retinal position error (RPE) of an intended target. Recently it has been discovered that PBN activity continues to enco...
Rui Ma, Todd P. Coleman, Joseph G. Malpeli
IWANN
2009
Springer
15 years 2 months ago
Easing the Smart Home: Translating Human Hierarchies to Intelligent Environments
Abstract. Ubiquitous computing research have extended traditional environments in the so–called Intelligent Environments. All of them use their capabilities for pursuing their in...
Manuel García-Herranz, Pablo A. Haya, Xavie...
NIPS
1996
14 years 10 months ago
Multidimensional Triangulation and Interpolation for Reinforcement Learning
Dynamic Programming, Q-learning and other discrete Markov Decision Process solvers can be applied to continuous d-dimensional state-spaces by quantizing the state space into an arr...
Scott Davies