Amos Storkey

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Amos James Storkey, a British computer scientist and reader (associate professor) at Institute for Adaptive and Neural Computation, School of Informatics, University of Edinburgh. He holds a Ph.D. in 1999 on neural networks from the Neural Systems Group, Department of Electrical Engineering, Imperial College London under Philippe De Wilde. His research covers machine learning applied to prediction market, astronomy and changing environments, bayesian modeling in neuroimaging, learning and inference, dynamical Boltzmann machine models, and scalable deep learning.

=DCNNs in Go= As reported in their 2014 paper Teaching Deep Convolutional Neural Networks to Play Go, Amos Storkey along with Christopher Clark trained an 8-layer convolutional neural network by supervised learning from a database of human professional games to predict the moves made by expert Go players. They introduced a number of novel techniques, including a method of tying weights in the network to 'hard code' symmetries that are expect to exist in the target function, and demonstrated in an ablation study they considerably improve performance. Their final networks can consistently defeat Gnu Go, indicating it is state of the art among programs that do not use Monte-Carlo Tree Search, and was also able to win some games against Fuego while using a fraction of the playing time .

=Selected Publications=

1997 ...

 * Amos Storkey (1997). Increasing the Capacity of a Hopfield Network without Sacrificing Functionality. ICANN 1997, pdf
 * Amos Storkey (1999). Efficient Covariance Matrix Methods for Bayesian Gaussian Processes and Hopfield Neural Networks. Ph.D. thesis, Imperial College London, supervisor Philippe De Wilde, CiteSeerX

2000 ...

 * Amos Storkey (2002). Dynamic Structure Super-Resolution. NIPS 2002
 * Amos Storkey (2003). Generalised Propagation for Fast Fourier Transforms with Partial or Missing Data. NIPS 2003
 * Mark Everingham, Andrew Zisserman, Chris Williams, Luc van Gool, Moray Allan, Amos Storkey, et al. (2005). The 2005 PASCAL Visual Object Classes Challenge. MLCW 2005, pdf
 * Amos Storkey, Masashi Sugiyama (2006). Mixture Regression for Covariate Shift. NIPS 2006
 * Lawrence Murray, Amos Storkey (2007). Continuous Time Particle Filtering for fMRI. NIPS 2007, pdf

2010 ...

 * Amos Storkey (2011). Machine Learning Markets. arXiv:1106.4509
 * Amos Storkey (2013). Dynamic Trees: A Structured Variational Method Giving Efficient Propagation Rules. arXiv:1301.3895
 * Christopher Clark, Amos Storkey (2014). Teaching Deep Convolutional Neural Networks to Play Go. arXiv:1412.3409
 * Christopher Clark, Amos Storkey (2015). Training Deep Convolutional Neural Networks to Play Go. ICML 2015, pdf
 * Harrison Edwards, Amos Storkey (2016). Towards a Neural Statistician. arXiv:1606.02185
 * Yuri Burda, Harrison Edwards, Amos Storkey, Oleg Klimov (2018). Exploration by Random Network Distillation. arXiv:1810.12894

=External Links=
 * Amos Storkey
 * Amos Storkey - Google Scholar Citations
 * Amos Storkey - The Mathematics Genealogy Project
 * Christopher Clark and Amos Storkey apply new algorithms to ancient Chinese game 'Go' - Edinburgh Research Explorer

=References= Up one level