Bob Durrant
Cited by
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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
Random projections as regularizers: learning a linear discriminant from fewer observations than dimensions
RJ Durrant, A Kabán
Machine Learning 99 (2), 257-286, 2015
Towards Large Scale Continuous EDA: A Random Matrix Theory Perspective
A Kabán, J Bootkrajang, RJ Durrant
Proceedings Genetic and Evolutionary Computation Conference (GECCO 2013), pp …, 2013
Compressed fisher linear discriminant analysis: classification of randomly projected data
RJ Durrant, A Kabán
Proceedings 16th ACM SIGKDD international conference on Knowledge discovery …, 2010
Sharp Generalization Error Bounds for Randomly-projected Classifiers
RJ Durrant, A Kaban
Proceedings 30th International Conference on Machine Learning, Atlanta …, 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
Error bounds for Kernel Fisher Linear Discriminant in Gaussian Hilbert space
RJ Durrant, A Kabán
Proceedings 15th International Conference on Artificial Intelligence and …, 0
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
Learning in high dimensions with projected linear discriminants
RJ Durrant
University of Birmingham, 2013
Linear dimensionality reduction in linear time: Johnson-lindenstrauss-type guarantees for random subspace
N Lim, RJ Durrant
arXiv preprint arXiv:1705.06408, 2017
Dimension-Adaptive Bounds on Compressive FLD Classification
A Kabán, RJ Durrant
Proceedings 24th International Conference on Algorithmic Learning Theory …, 0
Structure from randomness in halfspace learning with the zero-one loss
A Kabán, RJ Durrant
Journal of Artificial Intelligence Research 69, 733-764, 2020
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
A Diversity-aware Model for Majority Vote Ensemble Accuracy
NJS Lim, RJ Durrant
23rd International Conference on Artificial Intelligence and Statistics, 2020
Maximum margin principal components
X Luo, RJ Durrant
arXiv preprint arXiv:1705.06371, 2017
Random projections for machine learning and data mining: Theory and applications
RJ Durrant, A Kabán
ECML PKDD 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
Flip Probabilities for Random Projections of θ-separated Vectors
RJ Durrant, A Kabán
School of Computer Science Technical Reports, 2010
Foreword: special issue for the journal track of the 8th Asian conference on machine learning (ACML 2016)
RJ Durrant, KE Kim, G Holmes, S Marsland, M Sugiyama, ZH Zhou
Machine Learning 106 (5), 623-625, 2017
A norm-concentration argument for non-convex regularisation
A Kabán, RJ Durrant
ICML/UAI/COLT Workshop on Sparse Optimization and Variable Selection, 9 July …, 0
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