DR. JAMES A GRANT

Preprints

Covariance Decomposition for Distance Based Species Tree Estimation G. Aliatimis, R. Yoshida, B. Boyacı, J.A. Grant. (In Submission)

Apple Tasting Revisited: Bayesian Approaches to Partially Monitored Online Binary Classification J.A. Grant, D.S. Leslie. (In Submission)

Published / In Press

Federated X-armed Bandit with Flexible Personalisation A. Arabzadeh, J.A. Grant, D.S. Leslie. (2024) Transactions on Machine Learning Reserach.

Tropical Logistic Regression Model on Space of Phylogenetic Trees G. Aliatimis, R. Yoshida, B. Boyacı, J.A. Grant. (2024) Bulletin of Mathematical Biology.

Online Detection and Fuzzy Clustering of Anomalies in Non-Stationary Time Series C. He, D.S. Leslie, and J.A. Grant. (2024) Signals.

Learning to Rank under Multinomial Logit Choice J.A. Grant, D.S. Leslie. (2023) Journal of Machine Learning Research.

Sequential Simulation Optimization with Censoring: An Application to Bike Sharing Systems C. Gibbons, J.A. Grant, and R. Szechtman. (2023) In Proceedings of 2023 Winter Simulation Conference

Filtered Poisson Process Bandit on a Continuum J.A. Grant, R. Szechtman. (2021) European Journal of Operational Research

On Thompson Sampling for Smoother-than-Lipschitz Bandits J.A. Grant, D.S. Leslie. (2020) AISTATS Notable Paper Award Winner

Adaptive Policies for Perimeter Surveillance Problems J.A. Grant, D.S. Leslie, K. Glazebrook, R. Szechtman, A. Letchford. (2020) European Journal of Operational Research

Adaptive Sensor Placement For Continuous Spaces J.A. Grant, A. Boukouvalas, R. Griffiths, D.S. Leslie, S. Vakili, E. Munoz de Cote. (2019) ICML

Other

Poisson Process Bandits: Sequential Models and Algorithms for Maximising the Detection of Point Data J.A. Grant (2019, PhD Thesis)

Posterior Contraction Rates for Gaussian Cox Processes with Non-identically Distributed Data J.A. Grant, D.S. Leslie. (2019, Working Paper)

Combinatorial Bandits with Filtered Feedback J.A. Grant, D.S. Leslie, K. Glazebrook, R. Szechtman. (2017, Technical Report)

Bayesian Changepoint Detection in Solar Activity Data J.A. Grant (2014, Masters Thesis)

Technical Talks on Specific Papers

Apple Tasting Revisited - Cardiff University OR Department Seminar 2022 | Slides

Learning to Rank Under Multinomial Logit Choice - EcoSta 2022 | Slides

On Thompson Sampling for Smoother-than-Lipschitz Bandits - AISTATS 2020 | Recording | Slides

Online Learning: Applications in Surveillance and Quality Control - Naval Postgraduate School OR Department Seminar 2020 | Slides

Overviews and Lighter Introductions

Bandit Approaches to Balance Exploration and Exploitation - Nordic Personalisation Day 2023 (Keynote at Recommender Systems-focussed conference) | Recording (From 09:20) | Slides

Learning in Real-Time Fault Detection - NG-CDI Tech Talks 2022 (Research Talk for Broad Industrial Audience) | Recording | Slides

Intro to Multi-Armed Bandits - Tommy Flowers Network 2021 (Introductory Talk for Industry-Sponsored PhD Students)| Recording | Slides

Online Learning and Decision Making - Peak.ai Ensemble 2021 (Industry Webinar) | Recording | Slides

Current Students

Soheil Arabzadeh is a final year PhD student working with myself and David Leslie on bandits and online optimisation.

George Aliatimis is a final year PhD student working with myself, Burak Boyaci, and Ruriko Yoshida (Naval Postgraduate School) on tropical statistics.

Theo Crookes is a second year PhD student working with myself, Idris Eckley, and Lucy Gullon (BT) on bandits and anomaly detection.

Robert Lambert is a second year PhD student working with myself, Rob Shone, and Roberto Szechtman (Naval Postgraduate School) on sequential methods in simulation.

Adam Page is a second year PhD student working with myself, Anna-Lena Sachs, Chris Kirkbride, and Datasparq on safety in reinforcement learning.

Harry Newton is a first year PhD student, working with myself, Luke Rhodes-Leader, David Leslie, and Tesco on Bayesian optimisation.

Former Group Members

Changjiang He was a Senior Research Associate on the NG-CDI project working with myself and David Leslie on anomaly detection and clustering for telecommunications data. Changjiang's first role after leaving us was as a Lecturer in Computer Science and the University of Roehampton.