A Nonconformity Approach to Model Selection for SVMs (2009)
Hardoon, David R., Hussain, Zakria, Shawe-Taylor, John
We investigate the issue of model selection and the use of the nonconformity (strangeness) measure in batch learning. Using the nonconformity measure we propose a new training algorithm that helps...
Sparse Canonical Correlation Analysis (2009)
Hardoon, David R., Shawe-Taylor, John
We present a novel method for solving Canonical Correlation Analysis (CCA) in a sparse convex framework using a least squares approach. The presented method focuses on the scenario when one is...
Directed Acyclic Graph SVM with Decision Value History Smoothing (2009)
David R. Hardoon, Charanpal Dhanjal, Zakria Hussain
Data set V of the BCI competition is comprised of three tasks; that of imagination repetitive self-paced left and right hand movement and the generation of words beginning with the same random...
David R. Hardoon, Southampton So Bj, John Shawe-taylor, Southampton So Bj, Sandor Szedmak
In this paper we propose an approach to automatically annotate query
Generic object recognition by combining distinct features in machine (2008)
Hongying Meng, David R. Hardoon, John Shawe-taylor, Or Szedmak
learning
Information Retrieval by Inferring Implicit Queries from Eye Movements (2008)
David R. Hardoon, John Shawe-taylor
We introduce a new search strategy, in which the information retrieval (IR) query is inferred from eye movements measured when the user is reading text during an IR task. In training phase, we know...
Information Retrieval by Inferring Implicit Queries from Eye Movements (2008)
David R. Hardoon, John Shawe-taylor
We introduce a new search strategy, in which the information retrieval (IR) query is inferred from eye movements measured when the user is reading text during an IR task. In training phase, we know...
Generic object recognition by combining distinct features in machine (2008)
Hongying Meng, David R. Hardoon, John Shawe-taylor, Or Szedmak
learning
Using Image Stimuli to Drive fMRI Analysis (2008)
David R. Hardoon, Janaina Mourão-mir, Michael Brammer, Brain Image, Analysis Unit
Abstract. We introduce a new unsupervised fMRI analysis method based on Kernel Canonical Correlation Analysis which differs from the class of supervised learning methods that are increasingly being...
Stability Analysis of Kernel Canonical Correlation Analysis: Theory and Practice (2008)
David R. Hardoon, John Shawe-taylor
Canonical Correlation Analysis is a technique for finding pairs of basis vectors that maximise the correlation of a set of paired variables, these pairs can be considered as two views of the same...
David R. Hardoon, Michael Brammer, John Shawe-taylor
Here, we introduce a new unsupervised machine learning approach to fMRI analysis approach, in which the simple categorical description of stimulus type (e.g. type of task) is replaced by a more...
Louis Dorard, David R. Hardoon
London. It is substantially the result of my own work except where explicitly indicated in the text. The report will be distributed to the internal and external examiners, but thereafter may not be...
Sparse canonical correlation analysis (2007)
David R. Hardoon, Or Szedmak, John Shawe-taylor
overview with application to learning methods
Semantic Models for Machine Learning (2006)
In this thesis we present approaches to the creation and usage of semantic models by the analysis of the data spread in the feature space. We aim to introduce the general notion of using feature...
Semantic Models for Machine Learning (2006)
In this thesis we present approaches to the creation and usage of semantic models by the analysis of the data spread in the feature space. We aim to introduce the general notion of using feature...
Semantic Models for Machine Learning (2006)
In this thesis we present approaches to the creation and usage of semantic models by the analysis of the data spread in the feature space. We aim to introduce the general notion of using feature...
Two view learning: SVM-2K, theory and practice (2006)
Hongying Meng, Sandor Szedmak, David R. Hardoon, John Shawe-taylor
Kernel methods make it relatively easy to define complex highdimensional feature spaces. This raises the question of how we can identify the relevant subspaces for a particular learning task. When...
Two view learning: SVM-2K, theory and practice (2006)
Hongying Meng, Sandor Szedmak, David R. Hardoon, John Shawe-taylor
Kernel methods make it relatively easy to define complex highdimensional feature spaces. This raises the question of how we can identify the relevant subspaces for a particular learning task. When...
A correlation approach for automatic image annotation (2006)
David R. Hardoon, Craig Saunders, Or Szedmak
Abstract. The automatic annotation of images presents a particularly complex problem for machine learning researchers. In this work we experiment with semantic models and multi-class learning for the...
Generic object recognition by combining distinct features in machine learning (2005)
Meng, Hongying, Hardoon, David R., Szedmak, Sandor, Shawe-Taylor, John
In a genetic image object recognition or categorization system, the relevant features or descriptors from a characteristic point, patch or region of an image are often obtained by different...
One-class Machine Learning Approach for fMRI Analysis (2005)
Hardoon, David R, Manevitz, Larry M
One-Class Machine Learning techniques (i.e. "bottleneck" neural networks and one-class support vector machines (SVM)) are applied to classify whether a subject is performing a task or not by looking...
Generic object recognition by combining distinct features in machine learning (2005)
Meng, Hongying, Hardoon, David R., Shawe-Taylor, John, Szedmak, Sandor
In a generic image object recognition or categorization system, the relevant features or descriptors from a characteristic point, patch or region of an image are often obtained by different...
Generic object recognition by combining distinct features in machine learning (2005)
Meng, Hongying, Hardoon, David R., Szedmak, Sandor, Shawe-Taylor, John
In a genetic image object recognition or categorization system, the relevant features or descriptors from a characteristic point, patch or region of an image are often obtained by different...
One-class Machine Learning Approach for fMRI Analysis (2005)
Hardoon, David R, Manevitz, Larry M
One-Class Machine Learning techniques (i.e. "bottleneck" neural networks and one-class support vector machines (SVM)) are applied to classify whether a subject is performing a task or not by looking...
Generic object recognition by combining distinct features in machine learning (2005)
Meng, Hongying, Hardoon, David R., Shawe-Taylor, John, Szedmak, Sandor
In a generic image object recognition or categorization system, the relevant features or descriptors from a characteristic point, patch or region of an image are often obtained by different...
Generic object recognition by combining distinct features in machine learning (2005)
Meng, Hongying, Hardoon, David R., Szedmak, Sandor, Shawe-Taylor, John
In a genetic image object recognition or categorization system, the relevant features or descriptors from a characteristic point, patch or region of an image are often obtained by different...
One-class Machine Learning Approach for fMRI Analysis (2005)
Hardoon, David R, Manevitz, Larry M
One-Class Machine Learning techniques (i.e. "bottleneck" neural networks and one-class support vector machines (SVM)) are applied to classify whether a subject is performing a task or not by looking...
Generic object recognition by combining distinct features in machine learning (2005)
Meng, Hongying, Hardoon, David R., Shawe-Taylor, John, Szedmak, Sandor
In a generic image object recognition or categorization system, the relevant features or descriptors from a characteristic point, patch or region of an image are often obtained by different...
fmri analysis via one-class machine learning techniques (2005)
David R. Hardoon, Larry M. Manevitz
We show how one-class compression Neural Networks and one-class SVM can be applied to fMRI data to learn the classification of brain activity associated with a specific motor activity. For comparison...
Retrieving Keyword's to an Image Query using Kernel CCA (2004)
Hardoon, David R., Szedmak, Sandor, Shawe-Taylor, John
In this paper we propose an approach to automatically annotate queryimages with keywords. We use kernel Canonical Correlation Analysis to learn a semantic representation between images and their...
Multiclass classification by L1 norm Support Vector Machine (2004)
Szedmak, Sandor, Shawe-Taylor, John, Saunders, Craig .J., Hardoon, David .R.
The multiclass classification attracts a lot of attention in recent time. It has no such an elaborated theoretical foundation than the binary classification does. Rifkin et al. (2004)...
Using String Kernels to Identify Famous Performers from their Playing Style (2004)
Saunders, Craig, Hardoon, David R., Shawe-Taylor, John, Widmer, Gerhard
In this paper we show a novel application of string kernels: that is to the problem of recognising famous pianists from their style of playing. The characteristics of performers playing the same...
Using String Kernels to Identify Performers from their Playing Style (2004)
Hardoon, David R., Saunders, Craig, Shawe-Taylor, John, Widmer, Gerhard
In this paper we show a novel application of string kernels: that is to the problem of recognising famous pianists from their style of playing. The characteristics of performers playing the same...
Hardoon, David R, Shawe-Taylor, John, Friman, Ola
We use Kernel Canonical Correlation Analysis (KCCA) to infer brain activity in functional MRI by learning a semantic representation of fMRI brain scans and their associated activity signal. The...
KCCA Feature Selection for fMRI Analysis (2004)
Hardoon, David R, Shawe-Taylor, John, Friman, Ola
We use Kernel Canonical Correlation Analysis (KCCA) to infer brain activity in functional MRI by learning a semantic representation of fMRI brain scans and their associated activity signal. The...
Hardoon, David R, Shawe-Taylor, John, Friman, Ola
We use Kernel Canonical Correlation Analysis (KCCA) to infer brain activity in functional MRI by learning a semantic representation of fMRI brain scans and their associated activity signal. The...
Using String Kernels to Identify Famous Performers from their Playing Style (2004)
Saunders, Craig, Hardoon, David R., Shawe-Taylor, John, Widmer, Gerhard
In this paper we show a novel application of string kernels: that is to the problem of recognising famous pianists from their style of playing. The characteristics of performers playing the same...
Using String Kernels to Identify Performers from their Playing Style (2004)
Hardoon, David R., Saunders, Craig, Shawe-Taylor, John, Widmer, Gerhard
In this paper we show a novel application of string kernels: that is to the problem of recognising famous pianists from their style of playing. The characteristics of performers playing the same...
Hardoon, David R, Shawe-Taylor, John, Friman, Ola
We use Kernel Canonical Correlation Analysis (KCCA) to infer brain activity in functional MRI by learning a semantic representation of fMRI brain scans and their associated activity signal. The...
KCCA Feature Selection for fMRI Analysis (2004)
Hardoon, David R, Shawe-Taylor, John, Friman, Ola
We use Kernel Canonical Correlation Analysis (KCCA) to infer brain activity in functional MRI by learning a semantic representation of fMRI brain scans and their associated activity signal. The...
Hardoon, David R, Shawe-Taylor, John, Friman, Ola
We use Kernel Canonical Correlation Analysis (KCCA) to infer brain activity in functional MRI by learning a semantic representation of fMRI brain scans and their associated activity signal. The...
Using String Kernels to Identify Famous Performers from their Playing Style (2004)
Saunders, Craig, Hardoon, David R., Shawe-Taylor, John, Widmer, Gerhard
In this paper we show a novel application of string kernels: that is to the problem of recognising famous pianists from their style of playing. The characteristics of performers playing the same...
Using String Kernels to Identify Performers from their Playing Style (2004)
Hardoon, David R., Saunders, Craig, Shawe-Taylor, John, Widmer, Gerhard
In this paper we show a novel application of string kernels: that is to the problem of recognising famous pianists from their style of playing. The characteristics of performers playing the same...
Hardoon, David R, Shawe-Taylor, John, Friman, Ola
We use Kernel Canonical Correlation Analysis (KCCA) to infer brain activity in functional MRI by learning a semantic representation of fMRI brain scans and their associated activity signal. The...
KCCA Feature Selection for fMRI Analysis (2004)
Hardoon, David R, Shawe-Taylor, John, Friman, Ola
We use Kernel Canonical Correlation Analysis (KCCA) to infer brain activity in functional MRI by learning a semantic representation of fMRI brain scans and their associated activity signal. The...
Hardoon, David R, Shawe-Taylor, John, Friman, Ola
We use Kernel Canonical Correlation Analysis (KCCA) to infer brain activity in functional MRI by learning a semantic representation of fMRI brain scans and their associated activity signal. The...
Using string kernels to identify famous performers from their playing style (2004)
Craig Saunders, David R. Hardoon, John Shawe-taylor, Gerhard Widmer
In this chapter we show a novel application of string kernels: that is to the problem of recognising famous pianists from their style of playing. The characteristics of performers playing the same...
Using string kernels to identify famous performers from their playing style (2004)
Craig Saunders, David R. Hardoon, John Shawe-taylor, Gerhard Widmer
Abstract. In this paper we show a novel application of string kernels: that is to the problem of recognising famous pianists from their style of playing. The characterstics of performers playing the...
Canonical correlation analysis; An overview with application to learning methods (2003)
Hardoon, David R., Szedmak, Sandor, Shawe-Taylor, John
We present a general method using kernel Canonical Correlation Analysis to learn a semantic representation to web images and their associated text. The semantic space provides a common representation...
Canonical correlation analysis; An overview with application to learning methods (2003)
Hardoon, David R., Szedmak, Sandor, Shawe-Taylor, John
We present a general method using kernel Canonical Correlation Analysis to learn a semantic representation to web images and their associated text. The semantic space provides a common representation...
Canonical correlation analysis; An overview with application to learning methods (2003)
Hardoon, David R., Szedmak, Sandor, Shawe-Taylor, John
We present a general method using kernel Canonical Correlation Analysis to learn a semantic representation to web images and their associated text. The semantic space provides a common representation...
Vinokourov, Alexei, Hardoon, David R., Shawe-Taylor, John
We use kernel Canonical Correlation Analysis to learn a semantic representation of Web images and their associated text. This representation is used in two applications. In first application we...
Signal Extraction for Brain-Computer Interface (2003)
Hardoon, David R., Shawe-Taylor, John
We use Kernel Canonical Correlation Analysis (KCCA) for detecting brain activity in function MRI by learning a semantic representation of fMRI brain scans and their associated time frequency. The...
Vinokourov, Alexei, Hardoon, David R., Shawe-Taylor, John
We use kernel Canonical Correlation Analysis to learn a semantic representation of Web images and their associated text. This representation is used in two applications. In first application we...
Signal Extraction for Brain-Computer Interface (2003)
Hardoon, David R., Shawe-Taylor, John
We use Kernel Canonical Correlation Analysis (KCCA) for detecting brain activity in function MRI by learning a semantic representation of fMRI brain scans and their associated time frequency. The...
Vinokourov, Alexei, Hardoon, David R., Shawe-Taylor, John
We use kernel Canonical Correlation Analysis to learn a semantic representation of Web images and their associated text. This representation is used in two applications. In first application we...
Signal Extraction for Brain-Computer Interface (2003)
Hardoon, David R., Shawe-Taylor, John
We use Kernel Canonical Correlation Analysis (KCCA) for detecting brain activity in function MRI by learning a semantic representation of fMRI brain scans and their associated time frequency. The...
Alexei Vinokourov, David R. Hardoon, John Shawe-taylor
We use kernel Canonical Correlation Analysis to learn a semantic representation of Web images and their associated text. This representation is used in two applications. In first application we...
Kcca for different level precision in content-based image retrieval (2003)
David R. Hardoon, John Shawe-taylor
We use kernel Canonical Correlation Analysis to learn a semantic representation of web images and their associated text. In the application we look at two approaches of retrieving images based only...
Learning The Semantics Of Multimedia Content With Application To (2003)
Web Image Retrieval, Alexei Vinokourov, David R. Hardoon, John Shawe-taylor
We use kernel Canonical Correlation Analysis to learn a semantic representation of Web images and their associated text. This representation is used in two applications. In first application we...