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Machine learning

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Projects

Mean field games for cyber security

Implementing models of strategic decision-making in very large populations of small, randomly interacting agents, to analyse cyber-security threats

Making things simple before learning them

Developing ways of reducing the size of the 'environment' of certain machine learning problems to make them more manageable

Improving cystic fibrosis healthcare

Using machine learning techniques to help improve treatment plans for people living with the challenging symptoms of cystic fibrosis

Evaluating homomorphic encryption

Exploring different ways of encrypting sensitive data that can allow for secure, outsourced computation in the cloud

Distributed training for machine translation

Training neural networks, and developing related hardware, to be better at translating millions of words of online text

Data-driven nuclear management

Developing data-driven decision support systems to enable faster, more effective decision making for nuclear engineering operations

People queuing with one person's shadow highlighted

Co-designing algorithms and computer architecture

Designing hardware to suit the needs of data science algorithms, which will similarly be designed to suit the capabilities of the hardware

Publications and software

Research publications

On stochastic gradient Langevin dynamics with dependent data streams in the logconcave case

On stochastic gradient Langevin dynamics with dependent data streams in the logconcave case. Barkhagen, M.; Chau, N. H.; Moulines, É. ; Rásonyi, M. ; Sabanis, S.; Zhang, Y. Bernoulli 27(1): 1-33. 2021. DOI: 10.3150/19-BEJ1187

Research publications

The Tamed Unadjusted Langevin Algorithm

The Tamed Unadjusted Langevin Algorithm. Brosse, N., Durmus, A., Moulines, É. & Sabanis, S. In: Stochastic processes and their applications. 2019 ; Vol. 129, No. 10. pp. 3638-3663.

Research publications

On fixed gain recursive estimators with discontinuity in the parameters

On fixed gain recursive estimators with discontinuity in the parameters. Chau, H. N., Kumar, C., Rásonyi, M. & Sabanis, S. In : ESAIM: Probability and Statistics. 2019 ; Vol. 23. pp. 217-244

Research publications

Modeling Rape Reporting Delays Using Spatial, Temporal and Social Features

We present a novel approach to estimate the delay observed between the occurrence and...

Klemmer, K., Neill, D., Jarvis, S.A. 2018. “Modeling Rape Reporting Delays Using Spatial, Temporal and Social Features” NIPS Workshop on Modeling and Decision-Making in the Spatiotemporal Domain

Research publications

ColNet: Embedding the Semantics of Web Tables for Column Type Prediction

Automatically annotating column types with knowledge base (KB) concepts is a critical task to...

Jiaoyan Chen, Ernesto Jimenez-Ruiz, Ian Horrocks and Charles Sutton (2019). ColNet: Embedding the Semantics of Web Tables for Column Type Prediction. The Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19).

Research publications

Doubly Robust Bayesian Inference for Non-Stationary Streaming Data with β -Divergences

We present the very first robust Bayesian Online Changepoint Detection algorithm through General Bayesian...

Knoblauch, J., Jewson, J. & Damoulas T. (2018). Doubly Robust Bayesian Inference for Non-Stationary Streaming Data using β-Divergences. In Advances in Neural Information Processing Systems (NIPS 2018).

Research publications

Spatio-temporal Bayesian On-line Changepoint Detection with Model Selection

Bayesian On-line Changepoint Detection is extended to on-line model selection and non-stationary spatio-temporal processes...

Knoblauch, J. & Damoulas T. (2018). Spatio-temporal Bayesian On-line Changepoint Detection with Model Selection, International Conference on Machine Learning (ICML 2018).

Research publications