Robert J. Durrant

J. Artif. Intell. Res., 2020

A Diversity-aware Model for Majority Vote Ensemble Accuracy.

[BibT_eX]

[DOI]

Nick Jin Sean Lim

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2018

Foreword: special issue for the journal track of the 9th Asian Conference on Machine Learning (ACML 2017).

[BibT_eX]

[DOI]

Wee Sun Lee

Mach. Learn., 2018

Maximum Gradient Dimensionality Reduction.

[BibT_eX]

[DOI]

Xianghui Luo

Proceedings of the 24th International Conference on Pattern Recognition, 2018

2017

Foreword: special issue for the journal track of the 8th Asian conference on machine learning (ACML 2016).

[BibT_eX]

[DOI]

Mach. Learn., 2017

Maximum Margin Principal Components.

[BibT_eX]

[DOI]

Xianghui Luo

CoRR, 2017

2016

Toward Large-Scale Continuous EDA: A Random Matrix Theory Perspective.

[BibT_eX]

[DOI]

Jakramate Bootkrajang

Evol. Comput., 2016

How effective is Cauchy-EDA in high dimensions?

[BibT_eX]

[DOI]

Momodou L. Sanyang

Proceedings of the IEEE Congress on Evolutionary Computation, 2016

2015

Random projections as regularizers: learning a linear discriminant from fewer observations than dimensions.

[BibT_eX]

[DOI]

Mach. Learn., 2015

2013

Learning in high dimensions with projected linear discriminants.

[BibT_eX]

[DOI]

PhD thesis, 2013

Sharp Generalization Error Bounds for Randomly-projected Classifiers.

[BibT_eX]

[DOI]

Proceedings of the 30th International Conference on Machine Learning, 2013

Towards large scale continuous EDA: a random matrix theory perspective.

[BibT_eX]

[DOI]

Jakramate Bootkrajang

Proceedings of the Genetic and Evolutionary Computation Conference, 2013

Dimension-Adaptive Bounds on Compressive FLD Classification.

[BibT_eX]

[DOI]

Proceedings of the Algorithmic Learning Theory - 24th International Conference, 2013

Random Projections as Regularizers: Learning a Linear Discriminant Ensemble from Fewer Observations than Dimensions.

[BibT_eX]

[DOI]

Proceedings of the Asian Conference on Machine Learning, 2013

2012

A tight bound on the performance of Fisher's linear discriminant in randomly projected data spaces.

[BibT_eX]

[DOI]

Pattern Recognit. Lett., 2012

Error bounds for Kernel Fisher Linear Discriminant in Gaussian Hilbert space.

[BibT_eX]

[DOI]

Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

2010

Compressed fisher linear discriminant analysis: classification of randomly projected data.

[BibT_eX]

[DOI]

Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2010

A Bound on the Performance of LDA in Randomly Projected Data Spaces.

[BibT_eX]

[DOI]

Proceedings of the 20th International Conference on Pattern Recognition, 2010

2009

When is 'nearest neighbour' meaningful: A converse theorem and implications.

[BibT_eX]

[DOI]

J. Complex., 2009

2008

Learning with L<sub>q<1</sub> vs L<sub>1</sub>-Norm Regularisation with Exponentially Many Irrelevant Features.

[BibT_eX]

[DOI]