Stephen Roberts

MOrdReD: Memory-based Ordinal Regression Deep Neural Networks for Time Series Forecasting

Oct 24, 2018
Bernardo Pérez Orozco, Gabriele Abbati, Stephen Roberts

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* 30 pages, 12 figures * This version expands on the literature review; presents appendices in a graphical manner (as opposed to the previous tables); adds a mapping between dataset descriptions and shorthands; expands on results analysis and conclusions; corrects a few typos

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Equality Constrained Decision Trees: For the Algorithmic Enforcement of Group Fairness

Oct 10, 2018
Jack Fitzsimons, AbdulRahman Al Ali, Michael Osborne, Stephen Roberts

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* 8 pages, 2 figures, 1 page references, 1 page appendix

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Sequential sampling of Gaussian process latent variable models

Jul 20, 2018
Martin Tegner, Benjamin Bloem-Reddy, Stephen Roberts

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* In 2018 ICML Workshop on Tractable Probabilistic Models (TPM 2018)

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Extracting Predictive Information from Heterogeneous Data Streams using Gaussian Processes

Jul 11, 2018
Sid Ghoshal, Stephen Roberts

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* 15 pages, 5 figures, accepted for publication in Algorithmic Finance

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Entropic Spectral Learning in Large Scale Networks

Apr 18, 2018
Diego Granziol, Binxin Ru, Stefan Zohren, Xiaowen Dong, Michael Osborne, Stephen Roberts

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* 11 pages, 8 figures

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Gradient descent in Gaussian random fields as a toy model for high-dimensional optimisation in deep learning

Mar 24, 2018
Mariano Chouza, Stephen Roberts, Stefan Zohren

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* 10 pages, 10 figures

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VBALD - Variational Bayesian Approximation of Log Determinants

Feb 21, 2018
Diego Granziol, Edward Wagstaff, Bin Xin Ru, Michael Osborne, Stephen Roberts

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Safe Policy Search with Gaussian Process Models

Dec 15, 2017
Kyriakos Polymenakos, Alessandro Abate, Stephen Roberts

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* 5 pages, 2 figures, presented in the NIPS 2017 workshop "Transparent and Interpretable Machine Learning in Safety Critical Environments"

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