Henry W. J. Reeve

According to our database, Henry W. J. Reeve authored at least 24 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Structure discovery in PAC-learning by random projections.

Ata Kabán, Henry W. J. Reeve

Mach. Learn., July, 2024

Heterogeneous sets in dimensionality reduction and ensemble learning.

Henry W. J. Reeve, Ata Kabán, Jakramate Bootkrajang

Mach. Learn., April, 2024

An adaptive transfer learning perspective on classification in non-stationary environments.

Henry W. J. Reeve

CoRR, 2024

2023

Asymptotic Optimality for Decentralised Bandits.

Conor J. Newton, Ayalvadi Ganesh, Henry W. J. Reeve

Dyn. Games Appl., March, 2023

A Unified Theory of Diversity in Ensemble Learning.

Danny Wood, Tingting Mu, Andrew M. Webb, Henry W. J. Reeve, Mikel Luján, Gavin Brown

J. Mach. Learn. Res., 2023

Density Ratio Estimation and Neyman Pearson Classification with Missing Data.

Josh Givens, Song Liu, Henry W. J. Reeve

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2021

Optimal subgroup selection.

Henry W. J. Reeve, Timothy I. Cannings, Richard J. Samworth

CoRR, 2021

Adaptive transfer learning.

Henry W. J. Reeve, Timothy I. Cannings, Richard J. Samworth

CoRR, 2021

Statistical optimality conditions for compressive ensembles.

Henry W. J. Reeve, Ata Kabán

CoRR, 2021

2020

Optimistic bounds for multi-output prediction.

Henry W. J. Reeve, Ata Kabán

CoRR, 2020

Margin Maximization as Lossless Maximal Compression.

Nikolaos Nikolaou, Henry W. J. Reeve, Gavin Brown

CoRR, 2020

To Ensemble or Not Ensemble: When Does End-to-End Training Fail?

Andrew M. Webb, Charles Reynolds, Wenlin Chen, Henry W. J. Reeve, Dan-Andrei Iliescu, Mikel Luján, Gavin Brown

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2020

Optimistic Bounds for Multi-output Learning.

Henry W. J. Reeve, Ata Kabán

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Learning in high dimensions with asymmetric costs.

Henry W. J. Reeve

PhD thesis, 2019

Joint Training of Neural Network Ensembles.

Andrew M. Webb, Charles Reynolds, Dan-Andrei Iliescu, Henry W. J. Reeve, Mikel Luján, Gavin Brown

CoRR, 2019

Fast Rates for a kNN Classifier Robust to Unknown Asymmetric Label Noise.

Henry W. J. Reeve, Ata Kabán

Proceedings of the 36th International Conference on Machine Learning, 2019

Classification with unknown class-conditional label noise on non-compact feature spaces.

Henry W. J. Reeve, Ata Kabán

Proceedings of the Conference on Learning Theory, 2019

Exploiting geometric structure in mixture proportion estimation with generalised Blanchard-Lee-Scott estimators.

Henry W. J. Reeve, Ata Kabán

Proceedings of the Algorithmic Learning Theory, 2019

2018

Diversity and degrees of freedom in regression ensembles.

Henry W. J. Reeve, Gavin Brown

Neurocomputing, 2018

Modular Dimensionality Reduction.

Henry W. J. Reeve, Tingting Mu, Gavin Brown

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018

The K-Nearest Neighbour UCB Algorithm for Multi-Armed Bandits with Covariates.

Henry W. J. Reeve, Joe Mellor, Gavin Brown

Proceedings of the Algorithmic Learning Theory, 2018

2017

Degrees of Freedom in Regression Ensembles.

Henry W. J. Reeve, Gavin Brown

Proceedings of the 25th European Symposium on Artificial Neural Networks, 2017

Minimax rates for cost-sensitive learning on manifolds with approximate nearest neighbours.

Henry W. J. Reeve, Gavin Brown

Proceedings of the International Conference on Algorithmic Learning Theory, 2017

2015

Modular Autoencoders for Ensemble Feature Extraction.

Henry W. J. Reeve, Gavin Brown

Proceedings of the 1st Workshop on Feature Extraction: Modern Questions and Challenges, 2015