Gavin Brown
Gavin Brown
Professor of Machine Learning, Dept of Computer Science, University of Manchester
Verified email at manchester.ac.uk - Homepage
Title
Cited by
Cited by
Year
Diversity creation methods: a survey and categorisation
G Brown, J Wyatt, R Harris, X Yao
Information Fusion 6 (1), 5-20, 2005
10672005
Conditional Likelihood Maximisation: A Unifying Framework for Information Theoretic Feature Selection
G Brown, A Pocock, MJ Zhao, M LujŠn
Journal of Machine Learning Research 13 (1), 27-66, 2012
10142012
Managing diversity in regression ensembles.
G Brown, JL Wyatt, P Tino, Y Bengio
Journal of machine learning research 6 (9), 2005
3502005
Is feature selection secure against training data poisoning?
H Xiao, B Biggio, G Brown, G Fumera, C Eckert, F Roli
International Conference on Machine Learning, 1689-1698, 2015
2532015
Diversity in neural network ensembles
G Brown
University of Birmingham, 2004
2022004
A new perspective for information theoretic feature selection
G Brown
Artificial intelligence and statistics, 49-56, 2009
1892009
Ensemble Learning.
G Brown
Encyclopedia of Machine Learning 312, 2010
1662010
“good” and “bad” diversity in majority vote ensembles
G Brown, LI Kuncheva
International workshop on multiple classifier systems, 124-133, 2010
1412010
Learn++. MF: A random subspace approach for the missing feature problem
R Polikar, J DePasquale, HS Mohammed, G Brown, LI Kuncheva
Pattern Recognition 43 (11), 3817-3832, 2010
742010
An information theoretic perspective on multiple classifier systems
G Brown
International Workshop on Multiple Classifier Systems, 344-353, 2009
712009
On the Stability of Feature Selection Algorithms
S Nogueira, K Sechidis, G Brown
Journal of Machine Learning Research 18, 1-54, 2018
682018
Beyond Fano's inequality: Bounds on the optimal F-score, BER, and cost-sensitive risk and their implications
MJ Zhao, N Edakunni, A Pocock, G Brown
The Journal of Machine Learning Research 14 (1), 1033-1090, 2013
612013
Measuring the stability of feature selection
S Nogueira, G Brown
Joint European conference on machine learning and knowledge discovery in†…, 2016
582016
Intelligent selection of application-specific garbage collectors
J Singer, G Brown, I Watson, J Cavazos
Proceedings of the 6th international symposium on Memory management, 91-102, 2007
582007
Is deep learning safe for robot vision? adversarial examples against the icub humanoid
M Melis, A Demontis, B Biggio, G Brown, G Fumera, F Roli
Proceedings of the IEEE International Conference on Computer Vision†…, 2017
492017
Garbage collection auto-tuning for java mapreduce on multi-cores
J Singer, G Kovoor, G Brown, M LujŠn
ACM SIGPLAN Notices 46 (11), 109-118, 2011
492011
Fundamental nano-patterns to characterize and classify java methods
J Singer, G Brown, M LujŠn, A Pocock, P Yiapanis
Electronic Notes in Theoretical Computer Science 253 (7), 191-204, 2010
452010
Cost-sensitive boosting algorithms: Do we really need them?
N Nikolaou, N Edakunni, M Kull, P Flach, G Brown
Machine Learning 104 (2), 359-384, 2016
422016
Negative correlation learning and the ambiguity family of ensemble methods
G Brown, J Wyatt
International Workshop on Multiple Classifier Systems, 266-275, 2003
412003
ManTIME: Temporal expression identification and normalization in the TempEval-3 challenge
M Filannino, G Brown, G Nenadic
arXiv preprint arXiv:1304.7942, 2013
392013
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