Dr. David Hardoon at Google Scholar
1. Method of Diagnosing Autism Spectrum Disorder, GB Application GB1101200.2 filed 24/01/2011, PCT Patent Application PCT/GB2012/050135 filled on 23/01/2012
2. “An Analysis, Algorithm and Applications of Clustering and Co-occurrence Analysis” by Kristiaan Pelcksman and David R. Hardoon. 2010 [ PDF ]
3. “Pair-Wise Cluster Analysis” by David R. Hardoon and Kristiaan Pelcksman. 2010 [ PDF | arXiv ]
4. “Predicting Relevance of Parts of an Image” by Arto Klami, Samuel Kaski, Kitsuchart Pasupa, Sandor Szedmak, Steve Gunn, David R. Hardoon and Gabriela Csurka. Teknillinen Korkeakoulu, Pinview 2009 [ Link | PDF ]
5. “Ranking Algorithms for Implicit Feedback” by Kitsuchart Pasupa, Craig Saunders, Sandor Szedmak, Steve Gunn, David R. Hardoon, Arto Klami, Samuel Kaski, Alex Leung and Peter Auer. University of Southampton, Pinview 2009 [ Link | PDF ]
6. “A Nonconformity Approach to Model Selection for SVMs” by David R. Hardoon, Zakria Hussain and John Shawe-Taylor. University College London, Dept. of Computer Science 2009 [ Link | PDF | arXiv ]
7. “Sparse Canonical Correlation Analysis” by David R. Hardoon and John Shawe-Taylor. University College London, Dept. of Computer Science 2007 [ Link | PDF | arXiv ]
8. “Using Fisher Kernels and Hidden Markov Models for the Identification of Famous Composers from their Sheet Music” by David R. Hardoon, Craig Saunders and John Shawe-Taylor. Technical Report SOTON-TR-06-01, School of Electronics and Computer Science, ISIS Research Group, University of Southampton 2004 [ Link | PDF ]
9. “Generating Category-based Documents for Image Queries from Web-based Data Using Their Semantic Representation” by David R. Hardoon, Sandor Szedmak and John Shawe-Taylor. Technical Report SOTON-TR-05-07, School of Electronics and Computer Science, ISIS Research Group, University of Southampton 2004 [ Link | PDF ]
10. “KCCA Feature Selection for fMRI Analysis” by David R. Hardoon, John Shawe-Taylor and Ola Friman. Technical Report SOTON-TR-04-03, School of Electronics and Computer Science, ISIS Research Group, University of Southampton 2004 [ Link | PDF ]
11. “Canonical Correlation Analysis; An Overview with Application to Learning Methods” by David R. Hardoon, Sandor Szedmak and John Shawe-Taylor. Technical Report CSD-TR-03-02, Computer Science Dept. Royal Holloway, University of London 2003 [ Link | PDF ]
12. “Degree of abnormality in the fRMI response to sad facial expressions detected by one-class SVM correlates with Hamilton Rating Scale for Depression” by Janaina Mourão-Miranda, David R. Hardoon, Tim Hahn, Cindy Fu, John Shawe-Taylor and Michael Brammer. 16h Annual Meeting Human Brain Mapping (HBM) 2010 [ Link | PDF ]
13. "Trends and perspectives in music cognition research and technology" Hendrik Purwins and David R. Hardoon, Connection Science, Volume 21 (2-3), Pages 85-88, Nov 2010
14. “Guest Editorial: Learning from multiple sources” by Nicolò Cesa-Bianchi, David R. Hardoon and Gayle Leen. Machine Learning Journal: Special Issue on Learning From Multiple Sources, Volume 79 (1-2), Pages 1--3, 2010 [ Link | PDF ]
15. “Image Ranking with Eye Movements” by Kitsuchart Pasupa, Sandor Szedmak and David R. Hardoon. Advances in Ranking workshop, NIPS 2009 [ Link | PDF ]
16. “Support Vector Machine Model Selection Using Strangeness” by David R. Hardoon, Zakria Hussain and John Shawe-Taylor. 23rd European Conference on Operational Research (Machine Learning and Its Applications Stream) 2009 [ Link | PDF ]
17. “Editorial: Trends and Perspectives in Music Cognition Research and Technology” by Hendrik Purwins and David R. Hardoon, Connection Science, Special Issue on Music, Brain & Cognition, Volume 21 (2-3), Pages 85--88, 2009 [ Link | PDF ]
18. “One-Class Pattern Recognition in Brain Activity via Neural Networks” by Omer Boehm, David R. Hardoon and Larry Manevitz. 10th Bar-Ilan Symposium on Foundations of Artificial Intelligence (BISFAI) 2009 [ Link | PDF ]
19. “A Nonconformity Approach to Model Selection for SVMs” by David R. Hardoon, Zakria Hussain and John Shawe-Taylor. The Learning Workshop 2009 [ Link | PDF ]
20. “Accounting for Voxel Neighbourhood Relationship in the SVM” by David R. Hardoon, Janaina Mourão-Miranda, Vanessa Rocha Rega and John Shawe-Taylor. 15th Annual Meeting Human Brain Mapping (HBM) 2009 [ Link | PDF ]
21. “One Class SVM for Predicting Brain State” by Janaina Mourão-Miranda, David R. Hardoon, Joao R. Sato and Michael Brammer. 15th Annual Meeting Human Brain Mapping (HBM) 2009 [ Link | DOC ]
22. “Whole Genome Association Studies in Autistic Spectrum Disorders Revisited: A Support Vector Machine Approach” by P. Johnston, D. R. Hardoon, C. Ecker, T. K. Clarke, J. Powell and D. Murphy. The 8th Annual International Meeting for Autism Research (IMFAR) 2009 [ Link | PDF ]
23. “Marching Pursuit Kernel Fisher Discriminant Analysis” by Tom Diethe, Zakria Hussain, David R. Hardoon and John Shawe-Taylor. Sparsity in Machine Learning and Statistics Workshop 2009 [ Link | PDF ]
24. “The Double-Barrelled LASSO” by David R. Hardoon and John Shawe-Taylor. Learning from Multiple Sources Workshop, NIPS 2008 [ Link | PDF | Video ]
25. “Multiview Fisher Discriminant Analysis” by Tom Diethe, David R. Hardoon and John Shawe-Taylor. Learning from Multiple Sources Workshop, NIPS 2008 [ Link | PDF | Video ]
26. “Sparse Canonical Correlation Analysis” by David R. Hardoon and John Shawe-Taylor. Sparsity and Inverse Problems in Statistical Theory and Econometrics Workshop 2008 [ Link | PDF | Video ]
27. “Multivariate Analysis of Genetic Influence on Brain Volume” by Janaina Mourão-Miranda, David R. Hardoon, Ulrich Ettinger, Elena Antonova, David Collier, Veena Kumari, Steven C. R. Williams and Michael Brammer. I Congress IBRO/LARC of Neuroscience for Latin America, Caribbean and Iberian Peninsula 2008 [ Link | DOC ]
28. “An Investigation of the Visual Coding of Faces using Kernel Canonical Correlation Analysis” by N. Furl, D. R. Hardoon, J. Mourão-Miranda, N. Weiskopf, J. Shawe-Taylor and R. J. Dolan. 14th Annual Meeting Human Brain Mapping (HBM) 2008. [ Link | DOC ]
29. “Sparse CCA for Bilingual Word Generation” by David R. Hardoon and John Shawe-Taylor. EURO Mini Conference, Continuous Optimization and Knowledge-Based Technologies 2008 [ Link | TXT ]
30. “Can Style be Learned? A Machine Learning Approach Towards ‘Performing’ as Famous Pianists” by Louis Dorard, David R. Hardoon and John Shawe-Taylor. Music, Brain & Cognition Workshop, NIPS 2007 [ Link | PDF ]
31. “Neural Correlated of Tonality in Music” by Simon Durrant, David R. Hardoon, Edurado Reck Miranda, John Shawe-Taylor, Andre Brechmann and Henning Scheich. Music, Brain & Cognition Workshop, NIPS 2007 [ Link | PDF ]
32. “Unsupervised fMRI Analysis” by David R. Hardoon Janaina Mourão-Miranda, Michael Brammer and John Shawe-Taylor. 13th Annual Meeting Human Brain Mapping 2007. [ Link | PDF ]
33. “Maximum Margin Regression using KCCA Feature Projection” by David R. Hardoon and John Shawe-Taylor. Pittsburgh Brain Activity Interpretation Competition 2006. [ Link | PDF ]
34. “Unsupervised fMRI Analysis” by David R. Hardoon, Janaina Mourão-Miranda, Michael Brammer and John Shawe-Taylor. New Directions on Decoding Mental States from fMRI Data Workshop, NIPS 2006 [ Link | PDF | Video ]
35. “fMRI Analysis via One-Class Machine Learning Techniques” by David R. Hardoon and Larry M. Manevitz. Conference on Data Mining, Systems Analysis and Optimization in Neuroscience 2006. [ Link | Abstract ]
36. “Directed Acyclic Graph SVM with Decision Value History Smoothing” by David R. Hardoon, Charanpal Dhanjal and Zakria Hussian. BCI Competition III - Data set V, Methods acting on Longer Time Segments 2005. [ Link | PDF ]
37. “One-class Machine Learning Approach for fMRI Analysis” by David R. Hardoon and Larry M. Manevitz. Postgraduate Research Conference in Electronics, Photonics, Communications and Networks, and Computer Science (PREP) 2005. [ Link | PDF ]
38. “fMRI Analysis via One-class Machine Learning Techniques” by David R. Hardoon and Larry M. Manevitz. The 1st International Meeting of the Haifa Forum for Brain and Behaviour on: Neurobiology and Modulation of Memory Formation 2005 [ Link | PDF ]
39. “Classifying Cognitive Tasks to fMRI Data Using Machine Learning Techniques” by David R. Hardoon and Larry M. Manevitz. The 8th Biennial Israeli Symposium on the Foundations of Artificial Intelligence (BISFAI) 2005. [ Link | Abstract ]
40. “Novelty Detection and Kernel Canonical Correlation Analysis of Brain Activities in fMRI Images” by Alexander Dolia, David R. Hardoon and John Shawe-Taylor. Recent Advances in Modelling Spatio-Temporal Data Workshop 2005 [ Link | PDF ]
41. “Large Scale Multiclass Classification Based on Linear Optimization” by Sandor Szedmak, John Shawe-Taylor, Craig Saunders, and David R. Hardoon. Patter Recognition and Machine learning in Computer Vision Workshop 2004 [ Link | PDF | Video ]
42. “Signal Extraction for Brain-Computer Interface” by David R. Hardoon and John Shawe-Taylor. Machine Learning Meets the User Interface Workshop, NIPS 2003 [ Link | PDF ]
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