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