Publications

Neural Programmer−Interpreters
Scott Reed and Nando de Freitas
No. arXiv:1511.06279. 2015.
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Dueling Network Architectures for Deep Reinforcement Learning
Ziyu Wang‚ Nando de Freitas and Marc Lanctot
No. arXiv:1511.06581. 2015.
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Narrowing the Gap: Random Forests In Theory and In Practice
Misha Denil‚ David Matheson and Nando de Freitas
In International Conference on Machine Learning (ICML). 2014.
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Linear and Parallel Learning for Markov Random Fields
Yariv Dror Mizrahi‚ Misha Denil and Nando de Freitas
In International Conference on Machine Learning (ICML). 2014.
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Feedback from nature: an optimal distributed algorithm for maximal independent set selection
Alex Scott‚ Peter Jeavons and Lei Xu
In Panagiota Fatourou and Gadi Taubenfeld, editors, ACM Symposium on Principles of Distributed Computing‚ PODC '13‚ Montreal‚ QC‚ Canada‚ July 22−24‚ 2013. Pages 147−156. 2013.
Details about Feedback from nature: an optimal distributed algorithm for maximal independent set selection  BibTeX data for Feedback from nature: an optimal distributed algorithm for maximal independent set selection  DOI (10.1145/2484239.2484247)

An algebraic theory of complexity for discrete optimisation
David A. Cohen‚ Martin C. Cooper‚ Páidí Creed‚ Peter Jeavons and Stanislav Živný
In SIAM Journal on Computing. Vol. 42. No. 5. Pages 1915−1939. 2013.
Details about An algebraic theory of complexity for discrete optimisation  BibTeX data for An algebraic theory of complexity for discrete optimisation  DOI (10.1137/130906398)  Download (pdf) of An algebraic theory of complexity for discrete optimisation