Learning to Rank Images from Eye Movements (2009)
Pasupa, Kitsuchart, Saunders, Craig, Szedmak, Sandor, Klami, Arto, Kaski, Samuel, Gunn, Steve
Combining multiple information sources can improve the accuracy of search in information retrieval. This paper presents a new image search strategy which combines image features together with...
Can relevance of images be inferred from eye movements? (2009)
Pasupa, Kitsuchart, Klami, Arto, Saunders, Craig, De Campos, Teófilo, Kaski, Samuel
Searching for images from a large collection is a difficult task for automated algorithms. Many current techniques rely on items which have been manually 'tagged' with descriptors. This situation is...
Text Classification using String Kernels (2008)
Huma Lodhi, Craig Saunders, John Shawe-Taylor, Nello Cristianini, Chris Watkins
We propose a novel approach for categorizing text documents based on the use of a special kernel. The kernel is an inner product in the feature space generated by all subsequences of length k. A...
Can relevance of images be inferred from eye movements? (2008)
Klami, Arto, Saunders, Craig, De Campos, Teofilo E., Kaski, Samuel
Query formulation and efficient navigation through data to reach relevant results are undoubtedly major challenges for image or video retrieval. Queries of good quality are typically not available...
Can relevance of images be inferred from eye movements? (2008)
Klami, Arto, Saunders, Craig, De Campos, Teofilo, Kaski, Samuel
Query formulation and efficient navigation through data to reach relevant results are undoubtedly major challenges for image or video retrieval. Queries of good quality are typically not available...
Can relevance of images be inferred from eye movements? (2008)
Klami, Arto, Saunders, Craig, De Campos, Teofilo, Kaski, Samuel
Query formulation and efficient navigation through data to reach relevant results are undoubtedly major challenges for image or video retrieval. Queries of good quality are typically not available...
Juho Rousu, Sandor Szedmak, Craig Saunders, John Shawe-taylor
We present work in progress towards maximum margin hierarchical classification where the objects are allowed to belong to more than one category at a time. The classification hierarchy is represented...
Craig Saunders, Hauke Tschach, John Shawe-taylor
Recently, the use of string kernels that compare documents as a string of letters has been shown to achieve good results on text classification problems. In this paper we introduce the application of...
Learning Hierarchies at Two-class Complexity (2008)
Sandor Szedmak, Craig Saunders, John Shawe-taylor, Juho Rousu
It is assumed that to learn discriminative identification function when the output space is a labelled hierarchy is a much more complex problem than binary classification. In this presentation we...
A probabilistic framework for mismatch and profile (2008)
Alexei Vinokourov, Andrei N. Soklakov, Craig Saunders
string kernels
A Probabilistic Framework for Mismatch and Profile String Kernels (2008)
Alexei Vinokoufi Andrei, Andrei N. Soklakov, Craig Saunders
There has recently been nu merou applications of kernel methods in the field of bioinformatics. In particuT() the problem of protein homology has served as a benchmark for the performance of many new...
Using String Kernels to Identify Famous Performers from their Playing Style (2008)
Saunders, Craig, Hardoon, David, 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 Famous Performers from their Playing Style (2008)
Saunders, Craig, Hardoon, David, 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 Famous Performers from their Playing Style (2008)
Saunders, Craig, Hardoon, David, 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 Famous Performers from their Playing Style (2008)
Saunders, Craig, Hardoon, David, 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...
Text Classification using String Kernels Text Classification using String Kernels (2007)
Huma Lodhi, Craig Saunders, Nello Cristianini, Chris Watkins, Pack Kaelbling
We propose a novel approach for categorizing text documents based on the use of a special kernel. The kernel is an inner product in the feature space generated by all subsequences of length k. A...
Efficient Algorithms for Max-Margin Structured Classification (2007)
Rousu, Juho, Saunders, Craig, Szedmak, Sandor, Shawe-Taylor, John
Molecular Graph Kernels for Drug Discovery (2007)
Saunders, Craig, Demco, Anthony
We present some results on soft-matching graph kernels for the lead-hopping problem, as well as considering how one-class SVMs and subsampling of inactives perform for the computational difficult...
Using String Kernels to Identify Famous Performers from their Playing Style (2007)
Saunders, Craig, Hardoon, David, 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...
Kernel Methods: A paradigm for Pattern Analysis (2007)
Saunders, Craig, Cristianini, Nello, Shawe-Taylor, John
An introductory chapter describing how the use of kernel methods has become a paradigm for pattern analysis in many different application areas.
Cristianini, Nello, Shawe-Taylor, John, Saunders, Craig
This is a Kernel Methods overview/tutorial chapter.
Kernels for Strings and Graphs (2007)
Saunders, Craig, Demco, Anthony
This chapter provides an introduction to kernels for structures such as string and graphs, which can be used in a variety of kernel methods.
Graph Kernels for Molecular and Reduced Graphs (2007)
Saunders, Craig, Demco, Anthony
Poster displaying results of new soft-matching and gappy graph kernels using molecular and reduced graph representations.
Efficient algorithms for max-margin structured classification (2007)
Rousu, Juho, Saunders, Craig, Szedmak, Sandor, Shawe-Taylor, John
We present a general and efficient optimisation methodology for for max-margin sructured classification tasks. The efficiency of the method relies on the interplay of several techiques:...
Kernels for Strings and Graphs (2007)
Saunders, Craig, Demco, Anthony
This chapter gives an introduction to the use of structured kernels for data analayis. Specifically string kernels and graph kernels are reviewed, with some new ideas for processing the latter.
Efficient algorithms for max-margin structured classification (2006)
Saunders, Craig, Szedmak, Sandor, Shawe-Taylor, John, Rousu, Juho
We present a general and efficient optimization methodology for max-margin structured classification tasks. The efficiency of the method relies on the interplay of several techniques: formulation of...
Using String Kernels to Identify Famous Performers from their Playing Style (2006)
Saunders, Craig, Hardoon, David, Shawe-Taylor, John, Widmer, Gerhard
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...
Hierarchical Multilabel Classification, Juho Rousu, Craig Saunders, Sandor Szedmak, John Shawe-taylor, P. Bennett, ...
We present a kernel-based algorithm for hierarchical text classification where the documents are allowed to belong to more than one category at a time. The classification model is a variant of the...
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...
Learning Hierarchies at Two-class Complexity (2005)
Szedmak, Sandor, Saunders, Craig, Shawe-Taylor, John, Rousu, Juho
It is assumed that to learn discriminative identification function when the output space is a labelled hierarchy is a much more complex problem than binary classification. In this presentation we...
Learning Hierarchy via Embedding at Two-class Complexity (2005)
Szedmak, Sandor, Saunders, Craig, Shawe-Taylor, John, Rousu, Juho
Learning Hierarchy via Embedding at Two-class Complexity (2005)
Szedmak, Sandor, Saunders, Craig, Shawe-Taylor, John, Rousu, Juho
Kernel-based Learning of Hierarchical Multilabel Classification Models (2005)
Rousu, Juho, Saunders, Craig, Szedmak, Sandor, Shawe-Taylor, John
We present a kernel-based algorithm for hierarchical text classification where the documents are allowed to belong to more than one category at a time. The classification model is a variant of the...
A probabilistic framework for mismatch and profile string kernels (2005)
Vinokourov, A., Saunders, Craig, Soklakov, A.
There has recently been numerous applications of kernel methods in the field of bioinformatics. In particular, the problem of protein homology has served as a benchmark for the performance of many...
Using String Kernels to Identify Famous Performers from their Playing Style (2005)
Saunders, Craig, Hardoon, David, 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...
Learning Hierarchical Multi-Category Text Classification Models (2005)
Rousu, Juho, Saunders, Craig, Szedmak, Sandor, Shawe-Taylor, John
We present a kernel-based algorithm for hierarchical text classification where the documents are allowed to belong to more than one category at a time. The classification model is a variant of the...
A probabilistic framework for mismatch and profile string kernels. (2005)
Vinokourov, A., Soklakov, A., Saunders, Craig
There has recently been numerous applications of kernel methods in the field of bioinformatics. In particular, the problem of protein homology has served as a benchmark for the performance of many...
Hardoon, David, Saunders, Craig, Shawe-Taylor, John
We present a novel kernel which operates directly on the structural data of music notation. The characteristics of the composers writing style are obtained from note changes on a basic beat level,...
On Maximum Margin Hierarchical Multilabel Classification (2004)
Rousu, Juho, Saunders, Craig, Szedmak, Sandor, Shawe-Taylor, Prof John
We present work in progress towards maximum margin hierarchical classification where the objects are allowed to belong to more than one category at a time. The classification hierarchy is represented...
Multiclass classification by L1 norm Support Vector Machine (2004)
Szedmak, Sandor, Shawe-Taylor, John, Saunders, Craig, Hardoon, David
Multiclass classification by L1 norm Support Vector Machine (2004)
Szedmak, Sandor, Shawe-Taylor, John, Saunders, Craig, Hardoon, David
Using String Kernels to Identify Famous Performers from their Playing Style (2004)
Saunders, Craig, Hardoon, David, 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 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...
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...
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...
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...
On Maximum Margin Hierarchical Multilabel Classification (2004)
Juho Rousu, Sandor Szedmak, Craig Saunders, John Shawe-taylor
We present work in progress towards maximum margin hierarchical classification where the objects are allowed to belong to more than one category at a time. The classification hierarchy is represented...
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...
String kernels, Fisher kernels and finite state automata (2003)
Craig Saunders, John Shawe-taylor, Alexei Vinokourov
In this paper we show how the generation of documents can be thought of as a k-stage Markov process, which leads to a Fisher kernel from which the n-gram and string kernels can be re-constructed. The...
String kernels, Fisher kernels and finite state automata (2003)
Craig Saunders, John Shawe-taylor, Alexei Vinokourov
In this paper we show how the generation of documents can be thought of as a k-stage Markov process, which leads to a Fisher kernel from which the n-gram and string kernels can be re-constructed. The...
String kernels, Fisher kernels and finite state automata (2003)
Craig Saunders, John Shawe-taylor, Alexei Vinokourov
In this paper we show how the generation of documents can be thought of as a k-stage Markov process, which leads to a Fisher kernel from which the n-gram and string kernels can be re-constructed. The...
String kernels, Fisher kernels and finite state automata (2003)
Craig Saunders, John Shawe-taylor, Alexei Vinokourov
In this paper we show how the generation of documents can be thought of as a k-stage Markov process, which leads to a Fisher kernel from which the n-gram and string kernels can be re-constructed. The...
Text classification using string kernels (2002)
Huma Lodhi, Craig Saunders, John Shawe-taylor, Nello Cristianini, Chris Watkins, Bernhard Schölkopf
We propose a novel approach for categorizing text documents based on the use of a special kernel. The kernel is an inner product in the feature space generated by all subsequences of length k. A...
Syllables and other string kernel extensions (2002)
Recently, the use of string kernels that compare documents as a string of letters has been shown to achieve good results on text classification problems. In this paper we introduce the application of...
Text classification using string kernels (2002)
Huma Lodhi, Craig Saunders, Nello Cristianini, Chris Watkins, Bernhard Scholkopf
We propose a novel approach for categorizing text documents based on the use of a special kernel. The kernel is an inner product in the feature space generated by all subsequences of length k. A...
Text classification using string kernels (2002)
Huma Lodhi, Craig Saunders, Nello Cristianini, Chris Watkins, Bernhard Scholkopf
We propose a novel approach for categorizing text documents based on the use of a special kernel. The kernel is an inner product in the feature space generated by all subsequences of length k. A...
Text classification using string kernels (2002)
Huma Lodhi, Craig Saunders, John Shawe-taylor, Nello Cristianini, Chris Watkins, Bernhard Schölkopf
We propose a novel approach for categorizing text documents based on the use of a special kernel. The kernel is an inner product in the feature space generated by all subsequences of length k. A...
Text classification using string kernels (2002)
Huma Lodhi, Craig Saunders, John Shawe-taylor, Nello Cristianini, Chris Watkins, Bernhard Schölkopf
We propose a novel approach for categorizing text documents based on the use of a special kernel. The kernel is an inner product in the feature space generated by all subsequences of length k. A...
Comparing the bayes and typicalness frameworks (2001)
Thomas Melluish, Craig Saunders, Ilia Nouretdinov, Volodya Vovk
Abstract. When correct priors are known, Bayesian algorithms give optimal decisions, and accurate confidence values for predictions can be obtained. If the prior is incorrect however, these...
The typicalness framework: a comparison with the Bayesian approach (2001)
Thomas Melluish, Craig Saunders, Ilia Nouretdinov, Volodya Vovk
When correct priors are known, Bayesian algorithms give optimal decisions, and accurate confidence values for predictions can be obtained. If
Comparing the bayes and typicalness frameworks (2001)
Thomas Melluish, Craig Saunders, Ilia Nouretdinov, Volodya Vovk
Abstract. When correct priors are known, Bayesian algorithms give optimal decisions, and accurate condence values for predictions can be obtained. If the prior is incorrect however, these condence...
The typicalness framework: a comparison with the Bayesian approach (2001)
Thomas Melluish, Craig Saunders, Ilia Nouretdinov, Volodya Vovk
When correct priors are known, Bayesian algorithms give optimal decisions, and accurate confidence values for predictions can be obtained. If the prior is incorrect however, these confidence values...
Computationally efficient transductive machines (2000)
Craig Saunders, Alex Gammerman, Volodya Vovk
Abstract. In this paper 1 we propose a new algorithm for providing confidence and credibility values for predictions on a multi-class pattern recognition problem which uses Support Vector machines in...
Computationally efficient transductive machines (2000)
Craig Saunders, Alex Gammerman, Volodya Vovk
Abstract. In this paper we propose a new algorithm for providing confidence and credibility values for predictions on a multi-class pattern recognition problem which uses Support Vector machines in...
Machine-Learning Applications of Algorithmic Randomness (1999)
Volodya Vovk, Alex Gammerman, Craig Saunders
Most machine learning algorithms share the following drawback: they only output bare predictions but not the confidence in those predictions. In the 1960s algorithmic information theory supplied...
A Correlation Approach for Automatic Image Annotation (0006)
Hardoon, David, Saunders, Craig, Szedmak, Sandor, Shawe-Taylor, John
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...