Bob Durrant

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Ata KabanUniversity of Birmingham, School of Computer ScienceVerified email at bham.ac.uk
Jakramate BootkrajangDepartment of Computer Science, Chiang Mai UniversityVerified email at cmu.ac.th
Nick Lim Jin SeanUniversity of WaikatoVerified email at waikato.ac.nz
Jesse ReadÉcole PolytechniqueVerified email at polytechnique.edu
Albert BifetTélécom ParisTech & University of WaikatoVerified email at telecom-paristech.fr
Heitor Murilo GomesSenior Lecturer in AI, Victoria University of WellingtonVerified email at vuw.ac.nz
Greg CookDistinguished Professor in MicrobiologyVerified email at otago.ac.nz
Ray CursonsWaikato university, Massey UniversityVerified email at waikato.ac.nz
Vickery ArcusProfessor of Biological Sciences, University of WaikatoVerified email at waikato.ac.nz
Claire V. MulhollandResearch Assistant Professor, Albert Einstein College of MedicineVerified email at einsteinmed.edu
Momodou L SanyangUniversity of The Gambia (UTG)Verified email at utg.edu.gm
Stephen MarslandVictoria University of WellingtonVerified email at vuw.ac.nz
Geoffrey HolmesUniversity of WaikatoVerified email at waikato.ac.nz
Masashi SugiyamaDirector, RIKEN Center for Advanced Intelligence Project / Professor, The University of TokyoVerified email at k.u-tokyo.ac.jp
Zhi-Hua ZhouNanjing UniversityVerified email at nju.edu.cn
Kee-Eung KimKAISTVerified email at kaist.ac.kr
Xianghui LuoVerified email at mailbox.org
Wee Sun LeeProfessor, Department of Computer Science, National University of SingaporeVerified email at comp.nus.edu.sg

Bob Durrant

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Probabilistic Machine Learning Dimensionality Reduction Random Projections Measure Concentration


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When is "nearest neighbour" meaningful: A converse theorem and implications RJ Durrant, A Kabán Journal of Complexity 25 (4), 385-397, 2009	103	2009
Random projections as regularizers: Learning a linear discriminant from fewer observations than dimensions R Durrant, A Kabán Machine Learning 99 (2015), 257–286, 2014	84*	2014
Towards Large Scale Continuous EDA: A Random Matrix Theory Perspective A Kabán, J Bootkrajang, RJ Durrant Evolutionary Computation 24 (2), 255-291, 2016	81	2016
Compressed fisher linear discriminant analysis: classification of randomly projected data RJ Durrant, A Kabán Proceedings 16th ACM SIGKDD international conference on Knowledge discovery …, 2010	66	2010
Sharp Generalization Error Bounds for Randomly-projected Classifiers RJ Durrant, A Kaban Proceedings 30th International Conference on Machine Learning, Atlanta …, 2013	43	2013
Learning with L q< 1 vs L 1-Norm Regularisation with Exponentially Many Irrelevant Features A Kabán, R Durrant Proceedings European Conference on Machine Learning and Knowledge Discovery …, 2008	14	2008
A tight bound on the performance of Fisher’s linear discriminant in randomly projected data spaces RJ Durrant, A Kabán Pattern Recognition Letters 33 (7), 911-919, 2011	13	2011
Learning from evolving data streams through ensembles of random patches HM Gomes, J Read, A Bifet, RJ Durrant Knowledge and Information Systems 63 (7), 1597-1625, 2021	12	2021
Error bounds for Kernel Fisher Linear Discriminant in Gaussian Hilbert space RJ Durrant, A Kabán Proceedings 15th International Conference on Artificial Intelligence and …, 2012	12	2012
Rapid molecular diagnosis of the Mycobacterium tuberculosis Rangipo strain responsible for the largest recurring TB cluster in New Zealand CV Mulholland, A Ruthe, RT Cursons, R Durrant, N Karalus, K Coley, ... Diagnostic Microbiology and Infectious Disease 88 (2), 138-140, 2017	10	2017
Linear dimensionality reduction in linear time: Johnson-lindenstrauss-type guarantees for random subspace N Lim, RJ Durrant arXiv preprint arXiv:1705.06408, 2017	8	2017
How effective is Cauchy-EDA in high dimensions? ML Sanyang, RJ Durrant, A Kabán Proc. of the IEEE Congress on Evolutionary Computation (IEEE CEC 2016), 2016	8	2016
Dimension-Adaptive Bounds on Compressive FLD Classification A Kabán, RJ Durrant Proceedings 24th International Conference on Algorithmic Learning Theory …, 2013	7	2013
Learning in high dimensions with projected linear discriminants RJ Durrant University of Birmingham, 2013	7	2013
Structure from randomness in halfspace learning with the zero-one loss A Kabán, RJ Durrant Journal of Artificial Intelligence Research 69, 733-764, 2020	5*	2020
A Diversity-aware Model for Majority Vote Ensemble Accuracy NJS Lim, RJ Durrant 23rd International Conference on Artificial Intelligence and Statistics, 2020	5	2020
Random projections for machine learning and data mining: Theory and applications RJ Durrant, A Kabán ECML PKDD 4, 2012	4	2012
A bound on the performance of LDA in randomly projected data spaces RJ Durrant, A Kabán Proceedings 20th International Conference on Pattern Recognition (ICPR 2010 …, 2010	4	2010
Maximum margin principal components X Luo, RJ Durrant arXiv preprint arXiv:1705.06371, 2017	3	2017
Flip Probabilities for Random Projections of θ-separated Vectors RJ Durrant, A Kabán School of Computer Science Technical Reports, 2010	3	2010

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