· About me
· Publications and Presentations
I am a PhD student in the University of Birmingham School of Computer Science, supervised by Dr Ata Kaban.
I run the Measure Concentration reading group. We meet on Fridays at 13:00 in the Computer Science building – if you would like to attend please contact me for room details.
In 2008-9 I was a Teaching Fellow in the school and admissions tutor for our MSc Natural Computation and MSc Intelligent Systems Engineering degrees. I taught modules on Machine Learning, Machine Learning (Extended), Nature Inspired Design (A) and Nature Inspired Design. My old home page is here.
My Erdös number is 5.
Robert J. Durrant, Room 144,
School of Computer Science,
University of Birmingham,
Edgbaston,
B15 2TT
UK
e: r.j.durrant [at] cs [dot] bham [dot] ac [dot] uk
w: www.cs.bham.ac.uk/~durranrj
t: +44 (0)121 414 2884
I have a broad interest in learning and vision, both the organic and machine varieties.
I have a particular interest in computational theories of learning.
My current research is into dimensionality reduction. In particular, random projections of very high dimensional data sets into low dimensional spaces, and the effect of projection on classification performance.
Refereed Conference Papers:
R.J.Durrant and A. Kaban. Error bounds for Kernel Fisher Linear Discriminant in Gaussian Hilbert Space. Proceedings 15th International Conference on Artificial Intelligence and Statistics (AIStats 2012). To Appear. pdf
R.J.Durrant and A. Kaban. Compressed Fisher Linear Discriminant Analysis: Classification of Randomly Projected Data. Proceedings 16th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2010), pp 1119-1128. pdf poster (pdf) slides (pdf)
R.J.Durrant and A. Kaban. A bound on the performance of LDA in randomly projected data spaces. Proceedings 20th International Conference on Pattern Recognition (ICPR 2010). (Corrected) (IBM Best Student Paper Award in the Pattern Recognition and Machine Learning track.) pdf slides (pdf)
A. Kaban and R.J.Durrant. Learning with Lq<1 vs L1-norm regularization with exponentially many irrelevant features. Proc. of the 19th European Conference on Machine Learning (ECML08), 15-19 Sept 2008, Antwerp, Belgium. W. Daelemans et al. (eds.): LNAI 5211, pp. 580-596. Springer. pdf slides code
A. Kaban and R.J.Durrant. A norm-concentration argument for non-convex regularization. ICML/UAI/COLT Workshop on Sparse Optimization and Variable Selection, 9 July, 2008, Helsinki, Finland. pdf slides
Journal Papers:
R.J. Durrant and Ata Kaban. A tight bound on the performance of Fisher's linear discriminant in randomly projected data spaces. Pattern Recognition Letters (To Appear). pdf
R.J. Durrant and Ata Kaban. When Is 'Nearest Neighbor' Meaningful: A Converse Theorem and Implications. Journal of Complexity, 25(4), August 2009, pp 385-397. pdf
Invited Poster Presentation:
Sparsity in the context of learning from high dimensional data - with Ata Kaban. ICARN International Workshop 26 Sept 2008, Liverpool. pdf
Finite Sample Effects in Compressed Fisher's LDA - with Ata Kaban. 'Breaking News' poster presented at the 13th International Conference on Artificial Intelligence and Statistics (AIStats 2010) poster (pdf) proof (pdf)
R.J. Durrant and Ata Kaban. Flip Probabilities for Random Projections of θ-separated vectors. School Technical Report CSR-10-10. pdf
R.J. Durrant and Ata Kaban. A comparison of the moments of a quadratic form involving orthonormalised and normalised random projection matrices. School Technical Report CSR-10-10. pdf
Reviewing:
Pattern Recognition Letters (Elsevier)
Pattern Analysis and Applications (Springer)