David R. Hardoon

发表

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

Janaina Mourão Miranda, Michael J. Brammer, David R. Hardoon, 2011, NeuroImage.

Convergence analysis of kernel Canonical Correlation Analysis: theory and practice

John Shawe-Taylor, David R. Hardoon, J. Shawe-Taylor, 2008, Machine Learning.

DATA ANALYTICS AND PREDICTIVE ANALYTICS IN THE ERA OF BIG DATA

David R. Hardoon, Amy Shi‐Nash, 2016 .

Automatic Choice of Control Measurements

Samuel Kaski, Gayle Leen, David R. Hardoon, 2009, ACML.

Using Image Stimuli to Drive fMRI Analysis

Janaina Mourão Miranda, Michael J. Brammer, David R. Hardoon, 2007, ICONIP.

PAC-Bayes Analysis Of Maximum Entropy Classification

John Shawe-Taylor, David R. Hardoon, J. Shawe-Taylor, 2009, International Conference on Artificial Intelligence and Statistics.

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

John Shawe-Taylor, David R. Hardoon, Sándor Szedmák, 2005, NIPS.

Ranking algorithms for implicit feedback

Alex Po Leung, Kitsuchart Pasupa, Peter Auer, 2009 .

KCCA for different level precision in content-based image retrieval

David R. Hardoon, John Shawe-Taylor, 2003 .

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

David R. Hardoon, Larry M. Manevitz, Omer Boehm, 2011, Int. J. Mach. Learn. Cybern..

Information Retrieval by Inferring Implicit Queries from Eye Movements

John Shawe-Taylor, Samuel Kaski, Kai Puolamäki, 2007, AISTATS.

Centroid-Based Actionable 3D Subspace Clustering

Ghim-Eng Yap, Gao Cong, Suryani Lukman, 2013, IEEE Transactions on Knowledge and Data Engineering.

Image ranking with implicit feedback from eye movements

Kitsuchart Pasupa, David R. Hardoon, D. Hardoon, 2010, ETRA.

Design and Generalization Analysis of Orthogonal Matching Pursuit Algorithms

John Shawe-Taylor, David R. Hardoon, Charanpal Dhanjal, 2011, IEEE Transactions on Information Theory.

A metamorphosis of Canonical Correlation Analysis into multivariate maximum margin learning

Tijl De Bie, David R. Hardoon, Sándor Szedmák, 2007, ESANN.

Multiclass classification by L1 norm Support Vector Machine

John Shawe-Taylor, David R. Hardoon, Craig Saunders, 2004 .

KCCA for fMRI Analysis

David R. Hardoon, John Shawe-Taylor, Ola Friman, 2004 .

KCCA Feature Selection for fMRI Analysis

David R. Hardoon, John Shawe-Taylor, Ola Friman, 2004 .

Constructing Nonlinear Discriminants from Multiple Data Views

Tom Diethe, John Shawe-Taylor, David R. Hardoon, 2010, ECML/PKDD.

Support Vector Machine Model Selection Using Strangeness

John Shawe-Taylor, David R. Hardoon, Zakria Hussain, 2009 .

fMRI Analysis via One-class Machine Learning Techniques

David R. Hardoon, Larry M. Manevitz, D. Hardoon, 2005, IJCAI.

Guest Editorial: Learning from multiple sources

Nicolò Cesa-Bianchi, Gayle Leen, David R. Hardoon, 2010, Machine Learning.

Signal Extraction for Brain-Computer Interface

David R. Hardoon, John Shawe-Taylor, 2003, NIPS 2003.

One-class Machine Learning Approach for fMRI Analysis

David R. Hardoon, Larry M. Manevitz, D. Hardoon, 2005 .

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

David R. Hardoon, Chih-Chun Chen, D. Hardoon, 2010, J. Simulation.

Generating Category-based Documents for Image Queries from Web-based data using their Semantic Representation

David R. Hardoon, Sandor Szedmak, S John, 2005 .

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

John Shawe-Taylor, Eduardo Reck Miranda, David R. Hardoon, 2009, Connect. Sci..

Active learning with extremely sparse labeled examples

Shiliang Sun, David R. Hardoon, D. Hardoon, 2010, Neurocomputing.

LEARNING THE SEMANTICS OF MULTIMEDIA CONTENT WITH APPLICATION TO WEB IMAGE RETRIEVAL AND CLASSIFICATION

David R. Hardoon, John Shawe-Taylor, Alexei Vinokourov, 2003 .

Sparse canonical correlation analysis

John Shawe-Taylor, David R. Hardoon, J. Shawe-Taylor, 2009, Machine Learning.

2010 IEEE RADAR CONFERENCE

Tom Diethe, John Shawe-Taylor, David R. Hardoon, 2010 .

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

David R. Hardoon, Larry M. Manevitz, Omer Boehm, 2010, MICAI.

Canonical Correlation Analysis: An Overview with Application to Learning Methods

John Shawe-Taylor, David R. Hardoon, Sándor Szedmák, 2004, Neural Computation.

Combining Multiple Features for Product Categorisation by Multiple Kernel Learning

Kitsuchart Pasupa, David R. Hardoon, Chanawee Chavaltada, 2018 .

Matching Pursuit Kernel Fisher Discriminant Analysis

Tom Diethe, John Shawe-Taylor, David R. Hardoon, 2009, AISTATS.

Multiview Fisher Discriminant Analysis

Tom Diethe, John Shawe-Taylor, David R. Hardoon, 2008 .

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

John Shawe-Taylor, David R. Hardoon, J. Shawe-Taylor, 2010, Machine Learning.

Compressed Sampling for pulse Doppler radar

Tom Diethe, John Shawe-Taylor, Graeme E. Smith, 2010, 2010 IEEE Radar Conference.

Trends and perspectives in music cognition research and technology

Hendrik Purwins, David R. Hardoon, D. Hardoon, 2009, Connect. Sci..

Chapter 7 – Model Selection

John Shawe-Taylor, David R. Hardoon, Zakria Hussain, 2014 .

Image Ranking with Eye Movements

Kitsuchart Pasupa, David R. Hardoon, Sandor Szedmak, 2009 .

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

Alex Po Leung, John Shawe-Taylor, Kitsuchart Pasupa, 2010, ECML/PKDD.

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

Cuntai Guan, Zhuo Zhang, David R. Hardoon, 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

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

John Shawe-Taylor, Eduardo Reck Miranda, David R. Hardoon, 2009, Connect. Sci..

A Correlation Approach for Automatic Image Annotation

John Shawe-Taylor, David R. Hardoon, Sándor Szedmák, 2006, ADMA.

Semantic models for machine learning

David R. Hardoon, D. Hardoon, 2006 .

Can eyes reveal interest? Implicit queries from gaze patterns

John Shawe-Taylor, Samuel Kaski, Kai Puolamäki, 2009, User Modeling and User-Adapted Interaction.

A Comparative Study of Machine Learning Techniques for Automatic Product Categorisation

Kitsuchart Pasupa, David R. Hardoon, Chanawee Chavaltada, 2017, ISNN.

Unsupervised analysis of fMRI data using kernel canonical correlation

Janaina Mourão Miranda, Michael J. Brammer, David R. Hardoon, 2007, NeuroImage.

A Nonconformity Approach to Model Selection for SVMs

John Shawe-Taylor, David R. Hardoon, Zakria Hussain, 2009 .

Unsupervised fMRI Analysis

David R. Hardoon, D. Hardoon, 2006 .

The Double-Barrelled LASSO

John Shawe-Taylor, David R. Hardoon, J. Shawe-Taylor, 2008 .

Predicting relevance of parts of an image

Kitsuchart Pasupa, Gabriela Csurka, Samuel Kaski, 2009 .

Patient classi fi cation as an outlier detection problem : An application of the One-Class Support Vector Machine

John Shawe-Taylor, David R. Hardoon, Tim Hahn, 2011 .

Pair-Wise Cluster Analysis

David R. Hardoon, Kristiaan Pelcksman, 2010 .