These pages contain selected publications which serve as examples of the contributions by the researchers at Oxford and the ATI.

Publications by Oxford researchers funded by the Alan Turing Institute are included.

Learning to communicate to solve riddles with deep distributed recurrent Q-Networks

Date: 2016

Categories:

Reference

Foerster, J.N., Assael, Y.M., Freitas, N. and Whiteson, S. (2016) ‘Learning to communicate to solve riddles with deep distributed recurrent Q-Networks’.

Full text available at arxiv.org

Author

Prof. Nando de Freitas

The net as a knowledge machine: How the Internet became embedded in research

Date: 2016

Categories:

Reference

Meyer, E.T., Schroeder, R. and Cowls, J. (2016) ‘The net as a knowledge machine: How the Internet became embedded in research’, New Media & Society, . doi: 10.1177/1461444816643793.

Full text available at nms.sagepub.com

Author

Prof. Eric T. Meyer

Distance in the Forest Fire model how far are you from eve?

Date: 2016

Categories:

Reference

Kanade, V., Levi, R., Lotker, Z., Mallmann-Trenn, F. and Mathieu, C. (2016) ‘Distance in the Forest Fire model how far are you from eve?’, 27th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA 2016).

Full text available at www.cs.ox.ac.uk

Author

Dr. Varun Kanade

Preferential query answering in the semantic web with Possibilistic networks

Date: 2016

Categories:

Reference

Borgwardt, S., Fazzinga, B., Lukasiewicz, T., Shrivastava, A. and Tifrea-Marciuska, O. (2016) ‘Preferential query answering in the semantic web with Possibilistic networks’, 25th International Joint Conference on Artificial Intelligence‚ IJCAI 2016.

Full text available at lat.inf.tu-dresden.de

Author

Prof. Thomas Lukasiewicz

Consistency and fluctuations for stochastic gradient Langevin dynamics

Date: 2016

Categories:

Reference

Teh, Y.W., Thiery, A.H. and Vollmer, S.J. (2016) ‘Consistency and fluctuations for stochastic gradient Langevin dynamics’, Journal of Machine Learning Research, 17, pp. 1–33.

Full text available at www.jmlr.org

Author

Prof. Yee Whye Teh

Bayesian Learning of Kernel Embeddings

Date: 2016

Categories:

Reference

S. Flaxman, D. Sejdinovic, J. P. Cunningham, and S. Filippi, Bayesian Learning of Kernel Embeddings, in Uncertainty in Artificial Intelligence (UAI), 2016.

Full text available at www.auai.org

Authors

Prof. Dino Sejdinovic
Dr. Sarah Filippi

Global and local information in clustering labelled block models

Date: 2016

Categories:

Reference

Kanade, V., Mossel, E. and Schramm, T. (2016) ‘Global and local information in clustering labelled block models’, 18th International Workshop on Randomization and Computation (RANDOM 2014), . doi: 10.1109/TIT.2016.2516564.

No publisher link available

Author

Dr. Varun Kanade

Evaluating the Paper-to-Screen Translation of Participant-Aided Sociograms with High-Risk Participants

Date: 2016

Categories:

Reference

Hogan, B., Melville, J., Phillips II, G., Janulis, P., Contractor, N., Mustanski, B., & Birkett, M. (2016) ‘Evaluating the Paper-to-Screen Translation of Participant-Aided Sociograms with High-Risk Participants’, 2016 Conference on Human Factors in Computing.

Full text available at dl.acm.org

Author

Dr. Bernie Hogan

DR-ABC: Approximate Bayesian computation with kernel-based distribution regression

Date: 2016

Categories:

Reference

Mitrovic, J., Sejdinovic, D. and Teh, Y.W. (2016) ‘DR-ABC: Approximate Bayesian computation with kernel-based distribution regression’, International Conference on Machine Learning (ICML).

Full text available at arxiv.org

Authors

Prof. Dino Sejdinovic
Prof. Yee Whye Teh

First-Generation Students and College: The Role of Facebook Networks as Information Sources

Date: 2016

Categories:

Reference

Jeon, G. Y., Ellison, N. B., Hogan, B., & Greenhow, C. (2016) ‘First-Generation Students and College: The Role of Facebook Networks as Information Sources’, 2016 ACM Conference on Computer-Supported Cooperative Work and Social Computing.

Full text available at dl.acm.org

Author

Dr. Bernie Hogan