David R. Hardoon

Kelvin Sim, Ghim-Eng Yap, David R. Hardoon, Vivekanand Gopalkrishnan, Gao Cong, Suryani Lukman: Centroid-Based Actionable 3D Subspace Clustering. IEEE Trans. Knowl. Data Eng. 25(6): 1213-1226 (2013)

David R. Hardoon, John Shawe-Taylor: Sparse canonical correlation analysis. Machine Learning 83(3): 331-353 (2011)

Janaina Mourão Miranda, David R. Hardoon, Tim Hahn, Andre F. Marquand, Steven C. R. Williams, John Shawe-Taylor, Michael J. Brammer: Patient classification as an outlier detection problem: An application of the One-Class Support Vector Machine. NeuroImage 58(3): 793-804 (2011)

Zakria Hussain, John Shawe-Taylor, David R. Hardoon, Charanpal Dhanjal: Design and Generalization Analysis of Orthogonal Matching Pursuit Algorithms. IEEE Transactions on Information Theory 57(8): 5326-5341 (2011)

Shiliang Sun, David R. Hardoon: Active learning with extremely sparse labeled examples. Neurocomputing 73(16-18): 2980-2988 (2010)

C.-C. Chen, David R. Hardoon: Learning from multi-level behaviours in agent-based simulations: a Systems Biology application. J. Simulation 4(3): 196-203 (2010)

Nicolò Cesa-Bianchi, David R. Hardoon, Gayle Leen: Guest Editorial: Learning from multiple sources. Machine Learning 79(1-2): 1-3 (2010)

David R. Hardoon, John Shawe-Taylor: Decomposing the tensor kernel support vector machine for neuroscience data with structured labels. Machine Learning 79(1-2): 29-46 (2010)

David R. Hardoon, Kitsuchart Pasupa: Image ranking with implicit feedback from eye movements. ETRA 2010: 291-298

Omer Boehm, David R. Hardoon, Larry M. Manevitz: Towards One-Class Pattern Recognition in Brain Activity via Neural Networks. MICAI (2) 2010: 126-137

Tom Diethe, David R. Hardoon, John Shawe-Taylor: Constructing Nonlinear Discriminants from Multiple Data Views. ECML/PKDD (1) 2010: 328-343

Zakria Hussain, Alex Po Leung, Kitsuchart Pasupa, David R. Hardoon, Peter Auer, John Shawe-Taylor: Exploration-Exploitation of Eye Movement Enriched Multiple Feature Spaces for Content-Based Image Retrieval. ECML/PKDD (1) 2010: 554-569

Hendrik Purwins, David R. Hardoon: Trends and perspectives in music cognition research and technology. Connect. Sci. 21(2&3): 85-88 (2009)

Simon Durrant, David R. Hardoon, André Brechmann, John Shawe-Taylor, Eduardo R. Miranda, Henning Scheich: GLM and SVM analyses of neural response to tonal and atonal stimuli: new techniques and a comparison. Connect. Sci. 21(2&3): 161-175 (2009)

Simon Durrant, David R. Hardoon, André Brechmann, John Shawe-Taylor, Eduardo R. Miranda, Henning Scheich: GLM and SVM analyses of neural response to tonal and atonal stimuli: new techniques and a comparison. Connect. Sci. 21(4): 383 (2009)

Tom Diethe, Zakria Hussain, David R. Hardoon, John Shawe-Taylor: Matching Pursuit Kernel Fisher Discriminant Analysis. Journal of Machine Learning Research - Proceedings Track 5: 121-128 (2009)

John Shawe-Taylor, David R. Hardoon: PAC-Bayes Analysis Of Maximum Entropy Classification. Journal of Machine Learning Research - Proceedings Track 5: 480-487 (2009)

David R. Hardoon, John Shawe-Taylor: Convergence analysis of kernel Canonical Correlation Analysis: theory and practice. Machine Learning 74(1): 23-38 (2009)

Antti Ajanki, David R. Hardoon, Samuel Kaski, Kai Puolamäki, John Shawe-Taylor: Can eyes reveal interest? Implicit queries from gaze patterns. User Model. User-Adapt. Interact. 19(4): 307-339 (2009)

Gayle Leen, David R. Hardoon, Samuel Kaski: Automatic Choice of Control Measurements. ACML 2009: 206-219

Craig Saunders, David R. Hardoon, John Shawe-Taylor, Gerhard Widmer: Using string kernels to identify famous performers from their playing style. Intell. Data Anal. 12(4): 425-440 (2008)

David R. Hardoon, John Shawe-Taylor, Antti Ajanki, Kai Puolamäki, Samuel Kaski: Information Retrieval by Inferring Implicit Queries from Eye Movements. Journal of Machine Learning Research - Proceedings Track 2: 179-186 (2007)

Sándor Szedmák, Tijl De Bie, David R. Hardoon: A metamorphosis of Canonical Correlation Analysis into multivariate maximum margin learning. ESANN 2007: 211-216

David R. Hardoon, Janaina Mourão Miranda, Michael J. Brammer, John Shawe-Taylor: Using Image Stimuli to Drive fMRI Analysis. ICONIP (1) 2007: 477-486

David R. Hardoon, Craig Saunders, Sándor Szedmák, John Shawe-Taylor: A Correlation Approach for Automatic Image Annotation. ADMA 2006: 681-692

David R. Hardoon, Larry M. Manevitz: fMRI Analysis via One-class Machine Learning Techniques. IJCAI 2005: 1604-1605

Jason D. R. Farquhar, David R. Hardoon, Hongying Meng, John Shawe-Taylor, Sándor Szedmák: Two view learning: SVM-2K, Theory and Practice. NIPS 2005

David R. Hardoon, Sándor Szedmák, John Shawe-Taylor: Canonical Correlation Analysis: An Overview with Application to Learning Methods. Neural Computation 16(12): 2639-2664 (2004)

Craig Saunders, David R. Hardoon, John Shawe-Taylor, Gerhard Widmer: Using String Kernels to Identify Famous Performers from Their Playing Style. ECML 2004: 384-395