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Henry W. J. Reeve
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2020 – today
- 2024
- [j7]Zhanliang Huang, Ata Kabán, Henry W. J. Reeve:
Efficient learning with projected histograms. Data Min. Knowl. Discov. 38(6): 3948-4000 (2024) - [j6]Henry W. J. Reeve, Ata Kabán, Jakramate Bootkrajang:
Heterogeneous sets in dimensionality reduction and ensemble learning. Mach. Learn. 113(4): 1683-1704 (2024) - [j5]Ata Kabán, Henry W. J. Reeve:
Structure discovery in PAC-learning by random projections. Mach. Learn. 113(8): 5685-5730 (2024) - [i16]Henry W. J. Reeve:
An adaptive transfer learning perspective on classification in non-stationary environments. CoRR abs/2405.18091 (2024) - 2023
- [j4]Conor J. Newton, Ayalvadi Ganesh, Henry W. J. Reeve:
Asymptotic Optimality for Decentralised Bandits. Dyn. Games Appl. 13(1): 307-325 (2023) - [j3]Danny Wood, Tingting Mu, Andrew M. Webb, Henry W. J. Reeve, Mikel Luján, Gavin Brown:
A Unified Theory of Diversity in Ensemble Learning. J. Mach. Learn. Res. 24: 359:1-359:49 (2023) - [c11]Josh Givens, Song Liu, Henry W. J. Reeve:
Density Ratio Estimation and Neyman Pearson Classification with Missing Data. AISTATS 2023: 8645-8681 - [i15]Danny Wood, Tingting Mu, Andrew M. Webb, Henry W. J. Reeve, Mikel Luján, Gavin Brown:
A Unified Theory of Diversity in Ensemble Learning. CoRR abs/2301.03962 (2023) - [i14]Josh Givens, Song Liu, Henry W. J. Reeve:
Density Ratio Estimation and Neyman Pearson Classification with Missing Data. CoRR abs/2302.10655 (2023) - 2022
- [j2]Conor Newton, Ayalvadi Ganesh, Henry W. J. Reeve:
Asymptotic Optimality for Decentralised Bandits. SIGMETRICS Perform. Evaluation Rev. 49(2): 51-53 (2022) - 2021
- [i13]Henry W. J. Reeve, Ata Kabán:
Statistical optimality conditions for compressive ensembles. CoRR abs/2106.01092 (2021) - [i12]Henry W. J. Reeve, Timothy I. Cannings, Richard J. Samworth:
Adaptive transfer learning. CoRR abs/2106.04455 (2021) - [i11]Henry W. J. Reeve, Timothy I. Cannings, Richard J. Samworth:
Optimal subgroup selection. CoRR abs/2109.01077 (2021) - [i10]Conor Newton, Ayalvadi Ganesh, Henry W. J. Reeve:
Asymptotic Optimality for Decentralised Bandits. CoRR abs/2109.09427 (2021) - 2020
- [c10]Henry W. J. Reeve, Ata Kabán:
Optimistic Bounds for Multi-output Learning. ICML 2020: 8030-8040 - [c9]Andrew M. Webb, Charles Reynolds, Wenlin Chen, Henry W. J. Reeve, Dan-Andrei Iliescu, Mikel Luján, Gavin Brown:
To Ensemble or Not Ensemble: When Does End-to-End Training Fail? ECML/PKDD (3) 2020: 109-123 - [i9]Nikolaos Nikolaou, Henry W. J. Reeve, Gavin Brown:
Margin Maximization as Lossless Maximal Compression. CoRR abs/2001.10318 (2020) - [i8]Henry W. J. Reeve, Ata Kabán:
Optimistic bounds for multi-output prediction. CoRR abs/2002.09769 (2020)
2010 – 2019
- 2019
- [b1]Henry W. J. Reeve:
Learning in high dimensions with asymmetric costs. University of Manchester, UK, 2019 - [c8]Henry W. J. Reeve, Ata Kabán:
Exploiting geometric structure in mixture proportion estimation with generalised Blanchard-Lee-Scott estimators. ALT 2019: 682-699 - [c7]Henry W. J. Reeve, Ata Kabán:
Classification with unknown class-conditional label noise on non-compact feature spaces. COLT 2019: 2624-2651 - [c6]Henry W. J. Reeve, Ata Kabán:
Fast Rates for a kNN Classifier Robust to Unknown Asymmetric Label Noise. ICML 2019: 5401-5409 - [i7]Andrew M. Webb, Charles Reynolds, Dan-Andrei Iliescu, Henry W. J. Reeve, Mikel Luján, Gavin Brown:
Joint Training of Neural Network Ensembles. CoRR abs/1902.04422 (2019) - [i6]Henry W. J. Reeve, Ata Kabán:
Classification with unknown class conditional label noise on non-compact feature spaces. CoRR abs/1902.05627 (2019) - [i5]Henry W. J. Reeve, Ata Kabán:
Fast Rates for a kNN Classifier Robust to Unknown Asymmetric Label Noise. CoRR abs/1906.04542 (2019) - 2018
- [j1]Henry W. J. Reeve, Gavin Brown:
Diversity and degrees of freedom in regression ensembles. Neurocomputing 298: 55-68 (2018) - [c5]Henry W. J. Reeve, Joe Mellor, Gavin Brown:
The K-Nearest Neighbour UCB Algorithm for Multi-Armed Bandits with Covariates. ALT 2018: 725-752 - [c4]Henry W. J. Reeve, Tingting Mu, Gavin Brown:
Modular Dimensionality Reduction. ECML/PKDD (1) 2018: 605-619 - [i4]Henry W. J. Reeve, Gavin Brown:
Minimax rates for cost-sensitive learning on manifolds with approximate nearest neighbours. CoRR abs/1803.00310 (2018) - [i3]Henry W. J. Reeve, Gavin Brown:
Diversity and degrees of freedom in regression ensembles. CoRR abs/1803.00314 (2018) - [i2]Henry W. J. Reeve, Joe Mellor, Gavin Brown:
The K-Nearest Neighbour UCB algorithm for multi-armed bandits with covariates. CoRR abs/1803.00316 (2018) - 2017
- [c3]Henry W. J. Reeve, Gavin Brown:
Minimax rates for cost-sensitive learning on manifolds with approximate nearest neighbours. ALT 2017: 11-56 - [c2]Henry W. J. Reeve, Gavin Brown:
Degrees of Freedom in Regression Ensembles. ESANN 2017 - 2015
- [c1]Henry W. J. Reeve, Gavin Brown:
Modular Autoencoders for Ensemble Feature Extraction. FE@NIPS 2015: 242-259 - [i1]Henry W. J. Reeve, Gavin Brown:
Modular Autoencoders for Ensemble Feature Extraction. CoRR abs/1511.07340 (2015)
Coauthor Index
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last updated on 2024-11-08 21:30 CET by the dblp team
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