David MacKay
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Environment and Energy 
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Information Theory 
·Textbook 
·Gallager codes & MN codes 
·Theory of Sparse Graph codes 
·Regular Gallager codes 
·Irregular Gallager codes 
·Turbo codes  
·Insertions and deletions 
·Quantum Codes 
·Cryptanalysis and Coding 
·Discussion documents 
·More Message-Passing 
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Probabilistic Data Modelling 
·PhD thesis 
·Bayes for neural networks 
·ICA & Latent Variable Models 
·Bayes FAQ 
·Bayesian computations 
·Monte Carlo methods 
·Variational methods 
·Gaussian processes 
·Language, Proteins, Density nets 
·Images, Radar, Neuroscience 
·Materials science 
·Decision theory, Fair Elections « 
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Human-computer Interfaces 
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Computational Neuroscience 
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Evolution and Molecular Biology  
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Miscellaneous work 
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Errata 
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Software and Files 
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Recommendations 
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Any Problems? 


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Decision theory

_decision.ps | pdf | DJVU
Decision theory - a simple example

Reinforcement learning

RLcoin.ps.gz. RLcoin.pdf. abstract. | <- UK | Canada -> | RLcoin.ps.gz. RLcoin.pdf. abstract.
` Solution of a Toy Problem by Reinforcement Learning '.

Fair Elections

I26P3.pdf | abstract
Probabilistic electoral methods, representative probability, and maximum entropy.
Roger Sewell, David MacKay, Iain McLean
This paper was accepted (Dec 2008) for publication in Voting Matters. The published paper (Issue 26, January 2009) is available as a pdf file. | abstract
[This paper was formerly titled 'A maximum entropy approach to fair elections' RFSpdf.pdf (sorry, no longer available online)]

The Inference Group is supported by the Gatsby Foundation
and by a partnership award from IBM Zurich Research Laboratory
David J.C. MacKay
Site last modified Wed Nov 12 17:38:44 GMT 2014