David R. Hardoon

According to our database, David R. Hardoon authored at least 33 papers between 2004 and 2022.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2022

Antidiscrimination Laws, Artificial Intelligence, and Gender Bias: A Case Study in Nonmortgage Fintech Lending.

Stephanie Kelley, Anton Ovchinnikov, David R. Hardoon, Adrienne Heinrich

Manuf. Serv. Oper. Manag., 2022

2017

A Comparative Study of Machine Learning Techniques for Automatic Product Categorisation.

Chanawee Chavaltada, Kitsuchart Pasupa, David R. Hardoon

Proceedings of the Advances in Neural Networks - ISNN 2017 - 14th International Symposium, 2017

2013

Centroid-Based Actionable 3D Subspace Clustering.

Kelvin Sim, Ghim-Eng Yap, David R. Hardoon, Vivekanand Gopalkrishnan, Gao Cong, Suryani Lukman

IEEE Trans. Knowl. Data Eng., 2013

2012

Utilization of temporal information for intracranial pressure development trend forecasting in traumatic brain injury.

Mengling Feng, Zhuo Zhang, Cuntai Guan, David R. Hardoon, Nicolas Kon Kam King, Boon Chuan Pang, Beng Ti Ang

Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2012

2011

Design and Generalization Analysis of Orthogonal Matching Pursuit Algorithms.

Zakria Hussain, John Shawe-Taylor, David R. Hardoon, Charanpal Dhanjal

IEEE Trans. Inf. Theory, 2011

Patient classification as an outlier detection problem: An application of the One-Class Support Vector Machine.

Janaina Mourão Miranda, David R. Hardoon, Tim Hahn, Andre F. Marquand, Steven C. R. Williams, John Shawe-Taylor, Michael J. Brammer

NeuroImage, 2011

Classifying cognitive states of brain activity via one-class neural networks with feature selection by genetic algorithms.

Omer Boehm, David R. Hardoon, Larry M. Manevitz

Int. J. Mach. Learn. Cybern., 2011

Sparse canonical correlation analysis.

David R. Hardoon, John Shawe-Taylor

Mach. Learn., 2011

2010

Decomposing the tensor kernel support vector machine for neuroscience data with structured labels.

David R. Hardoon, John Shawe-Taylor

Mach. Learn., 2010

Guest Editorial: Learning from multiple sources.

Nicolò Cesa-Bianchi, David R. Hardoon, Gayle Leen

Mach. Learn., 2010

Learning from multi-level behaviours in agent-based simulations: a Systems Biology application.

Chih-Chun Chen, David R. Hardoon

J. Simulation, 2010

Active learning with extremely sparse labeled examples.

Shiliang Sun, David R. Hardoon

Neurocomputing, 2010

Exploration-Exploitation of Eye Movement Enriched Multiple Feature Spaces for Content-Based Image Retrieval.

Zakria Hussain, Alex Po Leung, Kitsuchart Pasupa, David R. Hardoon, Peter Auer, John Shawe-Taylor

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2010

Constructing Nonlinear Discriminants from Multiple Data Views.

Tom Diethe, David R. Hardoon, John Shawe-Taylor

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2010

Towards One-Class Pattern Recognition in Brain Activity via Neural Networks.

Omer Boehm, David R. Hardoon, Larry M. Manevitz

Proceedings of the Advances in Soft Computing, 2010

Image ranking with implicit feedback from eye movements.

David R. Hardoon, Kitsuchart Pasupa

Proceedings of the 2010 Symposium on Eye-Tracking Research & Applications, 2010

2009

Can eyes reveal interest? Implicit queries from gaze patterns.

Antti Ajanki, David R. Hardoon, Samuel Kaski, Kai Puolamäki, John Shawe-Taylor

User Model. User Adapt. Interact., 2009

Convergence analysis of kernel Canonical Correlation Analysis: theory and practice.

David R. Hardoon, John Shawe-Taylor

Mach. Learn., 2009

PAC-Bayes Analysis Of Maximum Entropy Classification.

John Shawe-Taylor, David R. Hardoon

Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

Matching Pursuit Kernel Fisher Discriminant Analysis.

Tom Diethe, Zakria Hussain, David R. Hardoon, John Shawe-Taylor

Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

Trends and perspectives in music cognition research and technology.

Hendrik Purwins, David R. Hardoon

Connect. Sci., 2009

GLM and SVM analyses of neural response to tonal and atonal stimuli: new techniques and a comparison.

Simon Durrant, David R. Hardoon, André Brechmann, John Shawe-Taylor, Eduardo R. Miranda, Henning Scheich

Connect. Sci., 2009

Automatic Choice of Control Measurements.

Gayle Leen, David R. Hardoon, Samuel Kaski

Proceedings of the Advances in Machine Learning, 2009

2008

Using string kernels to identify famous performers from their playing style.

Craig Saunders, David R. Hardoon, John Shawe-Taylor, Gerhard Widmer

Intell. Data Anal., 2008

2007

Unsupervised analysis of fMRI data using kernel canonical correlation.

David R. Hardoon, Janaina Mourão Miranda, Michael J. Brammer, John Shawe-Taylor

NeuroImage, 2007

Information Retrieval by Inferring Implicit Queries from Eye Movements.

David R. Hardoon, John Shawe-Taylor, Antti Ajanki, Kai Puolamäki, Samuel Kaski

Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics, 2007

Using Image Stimuli to Drive fMRI Analysis.

David R. Hardoon, Janaina Mourão Miranda, Michael J. Brammer, John Shawe-Taylor

Proceedings of the Neural Information Processing, 14th International Conference, 2007

A metamorphosis of Canonical Correlation Analysis into multivariate maximum margin learning.

Sándor Szedmák, Tijl De Bie, David R. Hardoon

Proceedings of the 15th European Symposium on Artificial Neural Networks, 2007

2006

Semantic models for machine learning.

David R. Hardoon

PhD thesis, 2006

A Correlation Approach for Automatic Image Annotation.

David R. Hardoon, Craig Saunders, Sándor Szedmák, John Shawe-Taylor

Proceedings of the Advanced Data Mining and Applications, Second International Conference, 2006

2005

Two view learning: SVM-2K, Theory and Practice.

Jason D. R. Farquhar, David R. Hardoon, Hongying Meng, John Shawe-Taylor, Sándor Szedmák

Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

fMRI Analysis via One-class Machine Learning Techniques.

David R. Hardoon, Larry M. Manevitz

Proceedings of the IJCAI-05, Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, Edinburgh, Scotland, UK, July 30, 2005

2004

Canonical Correlation Analysis: An Overview with Application to Learning Methods.

David R. Hardoon, Sándor Szedmák, John Shawe-Taylor

Neural Comput., 2004