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Ronald J. Williams

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2000 – 2009

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2009
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Wenxu Tong, Ying Wei, Leonel F. Murga, Mary Jo Ondrechen, Ronald J. Williams:
Partial Order Optimum Likelihood (POOL): Maximum Likelihood Prediction of Protein Active Site Residues Using 3D Structure and Sequence Properties. PLoS Comput. Biol. 5(1) (2009)

1990 – 1999

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1998
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Mohammad A. Al-Ansari, Ronald J. Williams:
Robust, Efficient, Globally-Optimized Reinforcement Learning with the Parti-Game Algorithm. NIPS 1998: 961-967
1996
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Jing Peng, Ronald J. Williams:
Incremental Multi-Step Q-Learning. Mach. Learn. 22(1-3): 283-290 (1996)
1994
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C. Lee Giles, Gary M. Kuhn, Ronald J. Williams:
Dynamic recurrent neural networks: Theory and applications. IEEE Trans. Neural Networks Learn. Syst. 5(2): 153-156 (1994)
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Jing Peng, Ronald J. Williams:
Incremental Multi-Step Q-Learning. ICML 1994: 226-232
1993
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Jing Peng, Ronald J. Williams:
Efficient Learning and Planning Within the Dyna Framework. Adapt. Behav. 1(4): 437-454 (1993)
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Jing Peng, Ronald J. Williams:
Efficient learning and planning within the Dyna framework. ICNN 1993: 168-174
1992
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Ronald J. Williams:
Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning. Mach. Learn. 8: 229-256 (1992)
1990
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Ronald J. Williams, Jing Peng:
An Efficient Gradient-Based Algorithm for On-Line Training of Recurrent Network Trajectories. Neural Comput. 2(4): 490-501 (1990)

1980 – 1989

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1989
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Ronald J. Williams, David Zipser:
A Learning Algorithm for Continually Running Fully Recurrent Neural Networks. Neural Comput. 1(2): 270-280 (1989)
1988
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Ronald J. Williams:
On the use of backpropagation in associative reinforcement learning. ICNN 1988: 263-270

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