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» Approximate Learning of Dynamic Models
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ICASSP
2011
IEEE
14 years 8 months ago
Scalable robust hypothesis tests using graphical models
Traditional binary hypothesis testing relies on the precise knowledge of the probability density of an observed random vector conditioned on each hypothesis. However, for many app...
Divyanshu Vats, Vishal Monga, Umamahesh Srinivas, ...
CIBCB
2006
IEEE
15 years 11 months ago
A Stochastic model to estimate the time taken for Protein-Ligand Docking
Abstract— Quantum mechanics and molecular dynamic simulation provide important insights into structural configurations and molecular interaction data today. To extend this atomi...
Preetam Ghosh, Samik Ghosh, Kalyan Basu, Sajal K. ...
COR
2008
142views more  COR 2008»
15 years 5 months ago
Application of reinforcement learning to the game of Othello
Operations research and management science are often confronted with sequential decision making problems with large state spaces. Standard methods that are used for solving such c...
Nees Jan van Eck, Michiel C. van Wezel
ICRA
2009
IEEE
227views Robotics» more  ICRA 2009»
15 years 11 months ago
Adaptive autonomous control using online value iteration with gaussian processes
— In this paper, we present a novel approach to controlling a robotic system online from scratch based on the reinforcement learning principle. In contrast to other approaches, o...
Axel Rottmann, Wolfram Burgard
173
Voted
SBRN
2000
IEEE
15 years 9 months ago
Non-Linear Modelling and Chaotic Neural Networks
This paper proposes a simple methodology to construct an iterative neural network which mimics a given chaotic time series. The methodology uses the Gamma test to identify a suita...
Antonia J. Jones, Steve Margetts, Peter Durrant, A...