• 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
  • “An Analysis, Algorithm and Applications of Clustering and Co-occurrence Analysis” by Kristiaan Pelcksman and David R. Hardoon. 2010 [ PDF ]
  • “Pair-Wise Cluster Analysis” by David R. Hardoon and Kristiaan Pelcksman. 2010 [ PDF | arXiv ]
  • “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 ]
  • “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 ]
  • “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 ]
  • “Sparse Canonical Correlation Analysis” by David R. Hardoon and John Shawe-Taylor. University College London, Dept. of Computer Science 2007 [ Link | PDF | arXiv ]
  • “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 ]
  • “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 ]
  • “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 ]
  • “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 ]
  • “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 ]
  • "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
  • “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 ]
  • “Image Ranking with Eye Movements” by Kitsuchart Pasupa, Sandor Szedmak and David R. Hardoon. Advances in Ranking workshop, NIPS 2009 [ Link | PDF ]
  • “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 ]
  • “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 ]
  • “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 ]
  • “A Nonconformity Approach to Model Selection for SVMs” by David R. Hardoon, Zakria Hussain and John Shawe-Taylor. The Learning Workshop 2009 [ Link | PDF ]
  • “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 ]
  • “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 ]
  • “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 ]
  • “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 ]
  • “The Double-Barrelled LASSO” by David R. Hardoon and John Shawe-Taylor. Learning from Multiple Sources Workshop, NIPS 2008 [ Link | PDF | Video ]
  • “Multiview Fisher Discriminant Analysis” by Tom Diethe, David R. Hardoon and John Shawe-Taylor. Learning from Multiple Sources Workshop, NIPS 2008 [ Link | PDF | Video ]
  • “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 ]
  • “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 ]
  • “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 ]
  • “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 ]
  • “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 ]
  • “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 ]
  • “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 ]
  • “Maximum Margin Regression using KCCA Feature Projection” by David R. Hardoon and John Shawe-Taylor. Pittsburgh Brain Activity Interpretation Competition 2006. [ Link | PDF ]
  • “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 ]
  • “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 ]
  • “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 ]
  • “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 ]
  • “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 ]
  • “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 ]
  • “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 ]
  • “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 ]
  • “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 ]

The Art of Data Science

My Publications

  • ”Centroid-based Actionable 3D Subspace Clustering”, Kelvin Sim, Ghim-Eng Yap, David R. Hardoon, Vivekanand Gopalkrishnan, Gao Cong and Suryani Lukman, IEEE Transactions on Knowledge and Data Engineering, Volume PP (99), 2012 [ Link | PDF ]
  • ”Business Analytics; Unleashing Latent Potential” David R. Hardoon, Synthesis Journal, Section 2, Pages 21-28, 2011 [ Link | PDF ]
  • ”Patient Classification as an Outlier Detection Problem: an Application of the One-Class Support Vector Machine” Janaina Mourao-Miranda, David R. Hardoon, Tim Hahn, John Shawe-Taylor, Steve C R Williams and Michael Brammer, NeuroImage,  Volume 58 (3), Pages 793-804, 2011 [ Link | PDF ]
  • ”Classifying Cognitive States of Brain Activity via One-Class Neural Networks with Feature Selection by Genetic Algorithms” Omer Boehm, David R. Hardoon and Larry M. Manevitz, International Journal of Machine Learning and Cybernetics, Volume 2 (3), Pages 125-134, 2011 [ Link | PDF ]
  • ”Sample Compression and Vapnik-Chervonenkis Bounds for Matching Pursuit” Zakria Hussain, John Shawe-Taylor, David R. Hardoon and Charanpal Dhanjal, IEEE Transactions on Information Theory, Volume 57 (8), Pages 5326-5341, 2011 [ Link | PDF ]
  • ”Sparse Canonical Correlation Analysis” David R. Hardoon and John Shawe-Taylor, Machine Learning Journal, Volume 83 (3), Pages 331-353, 2011 [ Link | PDF | Video ]
  • "Guest Editorial: Learning from multiple sources" Nicolo Cesa-Bianchi, David R. Hardoon and Gayle Leen, Machine Learning Journal, Volume 70 (1), Pages1-3, May 2010 [ Link ]
  • ”Active Learning with Extremely Sparse Labeled Examples” Shiliang Sun and David R. Hardoon, Neurocomputing, Volume 73 (16-18), Pages 2980--2988, 2010  [ Link | PDF ]
  • “Learning from Multi-Level Behaviours in Agent-Based Simulations: A Systems Biology Application” Chih-Chun Chen and David R. Hardoon, Journal of Simulation: Special Issue on Agent-Based Modelling, doi: 10.1057/jos.2009.30 , Volume 4, Pages 196--203, 2010 [ Link | PDF ]
  • “Decomposing the Tensor Kernel Support Vector Machine for Neuroscience Data with Structure Labels” David R. Hardoon and John Shawe-Taylor, Machine Learning Journal: Special Issue on Learning From Multiple Sources, Volume 79 (1-2), Pages 29--46, 2010 [ Link | PDF ]
  • “Can Eyes Reveal Interest? Implicit Queries from Gaze Patterns” Antti Ajanki, David R. Hardoon, Samuel Kaski, Kai Puolamaki and John Shawe-Taylor, User Modeling and User-Adapted Interaction: The Journal of Personalization Research, Volume 19 (4), Pages 307--339, 2009  [ Link | PDF ]
  • “GLM and SVM Analyses of Neural Response to Tonal and Atonal Stimuli: New Techniques and A Comparison” by Simon Durrant, David R. Hardoon, Andre Brechmann, John Shawe-Taylor, Edurado Reck Miranda and Henning Scheich, Connection Science, Special Issue on Music, Brain & Cognition, Volume 21 (2-3), Pages 161--175, 2009 [ Link | PDF ]
  • “Correlation Based Multivariate Analysis of Genetic Influence on Brain Volume” by David R. Hardoon, Ulrich Ettinger, Janaina Mourão-Miranda, Elena Antonova, David Collier, Veena Kumari, Steven C. R. Williams and Michael Brammer. Neuroscience Letters, Volume 450 (3), Pages 281--286, 2009 [ Link | PDF ]
  • “Convergence Analysis of Kernel Canonical Correlation Analysis: Theory and Practice” by David R. Hardoon and John Shawe-Taylor. Machine Learning Journal, Volume 74 (1), Pages 23--38, 2009 [ Link | PDF ]
  • “Using String Kernels to Identify Famous Performers from their Playing Style” by Craig Saunders, David R. Hardoon, John Shawe-Taylor and Gerhard Widmer. Intelligent Data Analysis, Volume 12(4), Pages 425--440, 2008 [ Link | PDF ]
  • “Unsupervised Analysis of fMRI Data Using Kernel Canonical Correlation” by David R. Hardoon, Janaina Mourão-Miranda, Michael Brammer and John Shawe-Taylor. NeuoImage, Volume 37 (4), Pages 1250--1259, 2007 [ Link | PDF ]
  • “Canonical Correlation Analysis: An Overview with Application to Learning Methods” by David R. Hardoon, Sandor Szedmak and John Shawe-Taylor. Neural Computation, Volume 16 (12), Pages 2639--2664, 2004 [ Link | PDF]
  • “Utilization of Temporal Information for Intracranial Pressure Development Trend Forecasting in Traumatic Brain Injury” by Mengling Feng, Zhuo Zhang, Cuntai Guan, Nicolas Kon Kam King, Boon Chuan Pang, Beng Ti Ang and David R. Hardoon. In Proceedings of 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2012 [ Link | PDF ]
  • “Towards One-Class Pattern Recognition in Brain Activity via Neural Networks” by Omer Boehm, David R. Hardoon and Larry Manevitz. In Proceedings of the 9th Mexican International Conference on Artificial Intelligence (MICAI), 2010 [ Link | PDF ]
  • “Utilization of Temporal Information for Intracranial Pressure Development Trend Forecasting in Traumatic Brain Injury” by Mengling Feng, Kuralmani Vellaisamy, Zhuo Zhang, David R. Hardoon, Pei Loon Chin, Cuntai Guan, Nicolas Kon Kam King, Kah Keow Lee, Boon Chuan Pang and Beng Ti Ang. In Proceedings of the 14th International Conference On Intracranial Pressure And Brain Monitoring (ICP), 2010 [ Link | PDF ]
  • “Constructing Nonlinear Discriminants from Multiple Data Views” by Tom Diethe, David R. Hardoon and John Shawe-Taylor. In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML), 2010 [ Link | PDF ]
  • “Exploration-Exploitation of Eye Movements Enriched Multiple Feature Spaces for Content-Based Image Retrieval” by Zakria Hussain, Alex P. Leung, Kitsuchart Pasupa, David R. Hardoon, Peter Auer and John Shawe-Taylor. In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML), 2010 [ Link | PDF ]
  • “Compressive Sampling for Pulse Doppler Radar” by Graeme E. Smith, Tom Diethe, Zakria Hussain, John Shawe-Taylor and David R. Hardoon. In Proceedings of the IEEE International Radar Conference, 2010 [ Link | PDF ]
  • “Image Ranking with Implicit Feedback from Eye Movements” by David R. Hardoon and Kitsuchart Pasupa. In Proceedings of the 6th Biennial Symposium on Eye Tracking Research & Applications (ETRA), 2010 [ Link | PDF ]
  • “Automatic Choice of Control Measurements” by Gayle Leen, David R. Hardoon and Samuel Kaski. In Proceedings of the 1st Asian Conference on Machine Learning (ACML). Zhi-Hua Zhou and Takashi Washio, Editors, Advances in Machine Learning (Lecture Notes in Artificial Intelligence 5828), Berlin: Springer, 2009 [ Link | PDF ]
  • “PAC-Bayes Analysis of Maximum Entropy Learning” by John Shawe-Taylor and David R. Hardoon. In Proceedings of the 12th International Conference on Artificial Intelligence and Statistics (AISTATS) 2009 [ Link | PDF ]
  • “Matching Pursuit Kernel Fisher Discriminant Analysis” by Tom Diethe, Zakria Hussain, David R. Hardoon and John Shawe-Taylor. In Proceedings of the 12th International Conference on Artificial Intelligence and Statistics (AISTATS) 2009 [ Link | PDF ]
  • “Using Image Stimuli to Drive fMRI Analysis” by David R. Hardoon, Janaina Mourão-Miranda, Michael Brammer and John Shawe-Taylor. The 14th International Conference on Neural Information Processing (ICONIP) 2007. In Springer LNCS 4984, Pages 477--486 [ Springer | Link | PDF ]
  • “A Metamorphosis of Canonical Correlation Analysis into Multivariate Maximum Margin Learning” by Sandor Szedmak, Tijl De Bie and David R. Hardoon. In Proceedings of the 15th European Symposium on Artificial Neural Networks (ESANN), 2007. [ Link | PDF ]
  • “Information Retrieval by Inferring Implicit Queries from Eye Movements” by David R. Hardoon, Antti Ajanki, Kai Puolamaki, John Shawe-Taylor and Samuel Kaski. In Proceedings of the 11th International Conference on Artificial Intelligence and Statistics (AISTATS) 2007 [ Link | PDF ]
  • “A Correlation Approach for Automatic Image Annotation” by David R. Hardoon, Craig Saunders, Sandor Szedmak and John Shawe-Taylor. The 2nd International Conference on Advanced Data Mining and Applications (ADMA) 2006. In Springer LNAI 4093, Pages 681--692 [ Springer | Link | PDF ]
  • “Two View Learning: SVM-2K, Theory and Practice” by Jason D. R. Farquhar, David R. Hardoon, Hongying Meng, John Shawe-Taylor and Sandor Szedmak. In Proceedings of 19th Annual Conference on Neural Information Processing Systems (NIPS) 2005. [ Link | PDF ]
  • “fMRI Analysis via One-class Machine Learning Techniques” by David R. Hardoon and Larry M. Manevitz. In Proceedings of the 19th International Joint Conference on Artificial Intelligence (IJCAI) 2005. Pages 1604--1606 [ Link | PDF ]
  • “Generic Object Recognition by Distinct Features Combination in Machine Learning” by Hongying Meng, David R. Hardoon, John Shawe-Taylor and Sandor Szedmak. 17th Annual Symposium on Electronic Imaging (EI111) 2005. In Proceedings of SPIE, Volume 5673, Pages 90--98 [ Link | PDF ]
  • A plagarised copy of the above paper has been detected: “Generic Object Recognition via Integrating Distinct Features with SVM” In Proceedings of the 5th International Conference on Machine Learning and Cybernetics, Dalian, 13-16 August 2006 “by” Tong-Cheng Huang and You-Dong Ding [ Link | PDF ]
  • “Using String Kernels to Identify Performers from their Playing Style” by Craig Saunders, David R. Hardoon, John Shawe-Taylor and Gerhard Widmer. In Proceedings of 15th European Conference on Machine Learning (ECML) 2004 [ Link | PDF ] -- Best Paper Award
  • “KCCA for fMRI Analysis” by David R. Hardoon, John Shawe-Taylor and Ola Friman. In Proceeding of Medical Image Understanding and Analysis (MIUA) 2004 [ Link | PDF ]
  • “KCCA for different level precision in content-based image retrieval” by David R. Hardoon and John Shawe-Taylor. In Proceedings of 3rd International Workshop on Content-Based Multimedia Indexing (CBMI), 2003 [ Link | PDF ]
  • “Learning the Semantics of Multimedia Content with Application to Web Image Retrieval and Classification” by Alexei Vinokourov, David R. Hardoon and John Shawe-Taylor. In Proceedings of 4th International Symposium on Independent Component Analysis (ICA) 2003 [ Link | PDF ]

contact me for copies of papers

Dr. David R. Hardoon © All rights reserved.

David Roi Hardoon, Ph.d.

Blogs

& News Articles

Journal Manuscripts

& Proceedings Manuscripts

BookS

& Contributed Book Chapters

TECHNICAL rEPORTS

& Others

  1. "Data Analytics and Predictive Analytics in the Era of Big Data" by Amy Shi-Nash and David R. Hardoon, contributed chapter in "Internet of Things & Data Analytics Handbook", John Wiley & Sons, First Edition 2016, ISBN: 978-1119173649
  2. "Model Selection" by David R. Hardoon, Zakria Hussain and John Shawe-Talyor, contributed chapter 7 in "Conformal Prediction for Reliable Machine Learning" by Vladimir Vovk, Shen-Shyang Ho, Vineeth Balasubramanian, Elsevier Science, April 2014, ISBN: 978-0123985378
  3. Getting Started with Business Analytics: Insightful Decision Making”, by David R. Hardoon and Galit Shmueli, Chapman and Hall/CRC, Mar 2013, ISBN: 978-1439896532, eBook: 978-1439896549
  4. "Semantic Models for Machine Learning" by David R. Hardoon, PhD Thesis, University of Southampton, School of Electronics and Computer Science, Feb 2006