Craig Saunders

发表

Kernels for Strings and Graphs

Craig Saunders, Anthony A. Demco, C. Saunders, 2007, Perspectives of Neural-Symbolic Integration.

Ridge Regression Learning Algorithm in Dual Variables

Alexander Gammerman, Vladimir Vovk, Craig Saunders, 1998, ICML.

Molecular Graph Kernels for Drug Discovery

Craig Saunders, Anthony A. Demco, Anthony Demco, 2007 .

Learning moods and emotions from color combinations

Gabriela Csurka, Craig Saunders, Luca Marchesotti, 2010, ICVGIP '10.

Proceedings of the 2005 international conference on Subspace, Latent Structure and Feature Selection

Marko Grobelnik, John Shawe-Taylor, Steve R. Gunn, 2005 .

The application of structured learning in natural language processing

Mahesan Niranjan, Sándor Szedmák, Craig Saunders, 2010, Machine Translation.

Handling phrase reorderings for machine translation

Mahesan Niranjan, Sándor Szedmák, Craig Saunders, 2009, ACL/IJCNLP.

Ranking algorithms for implicit feedback

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

Kernel Methods: A Paradigm for Pattern Analysis

Nello Cristianini, John Shawe-Taylor, Nello Cristianini, 2006 .

Learning Hierarchy via Embedding at Two-class Complexity

Juho Rousu, John Shawe-Taylor, Craig Saunders, 2005 .

Sentence-level confidence estimation for MT

Nello Cristianini, Lucia Specia, John Shawe-Taylor, 2009, EAMT.

Improving the Confidence of Machine Translation Quality Estimates

Lucia Specia, John Shawe-Taylor, Zhuoran Wang, 2009, MTSUMMIT.

Support Vector Machine Reference Manual

Alexander J. Smola, Craig Saunders, Weston J Stitson Mo, 1998 .

Using string kernels to identify famous performers from their playing style

John Shawe-Taylor, Gerhard Widmer, Craig Saunders, 2004, Intell. Data Anal..

Data-Driven Vehicle Identification by Image Matching

Raja Bala, José A. Rodríguez-Serrano, Florent Perronnin, 2012, ECCV Workshops.

Subspace, Latent Structure and Feature Selection techniques

Marko Grobelnik, John Shawe-Taylor, John Shawe-Taylor, 2006 .

Multiclass classification by L1 norm Support Vector Machine

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

String Kernels, Fisher Kernels and Finite State Automata

John Shawe-Taylor, Craig Saunders, Alexei Vinokourov, 2002, NIPS.

A Study on Perceptually Coherent Distance Measures for Color Schemes

Gabriela Csurka, Craig Saunders, Luca Marchesotti, 2011, Color Imaging Conference.

The typicalness framework: a comparison with the Bayesian approach

Vladimir Vovk, Ilia Nouretdinov, Craig Saunders, 2004 .

Description, analysis and evaluation of confidence estimation procedures for sub-categorisation

Jorma Laaksonen, John Shawe-Taylor, Kitsuchart Pasupa, 2009 .

2009 INTERNATIONAL CONFERENCE ON ADVANCED INFORMATION NETWORKING AND APPLICATIONS WORKSHOPS: WAINA, VOLS 1 AND 2

Craig Saunders, Bassam Farran, 2009, AINA 2009 2009.

Image simulation for automatic license plate recognition

Raja Bala, José A. Rodríguez-Serrano, Vladimir Kozitsky, 2012, Other Conferences.

A probabilistic framework for mismatch and profile string kernels

Craig Saunders, Alexei Vinokourov, Andrei N. Soklakov, 2005, ESANN.

Kernel regression for fMRI pattern prediction

John Ashburner, Craig Saunders, Yizhao Ni, 2011, NeuroImage.

Learning to rank images from eye movements

Kitsuchart Pasupa, Samuel Kaski, Steve R. Gunn, 2009, 2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops.

Subspace, Latent Structure and Feature Selection: Statistical and Optimization Perspectives Workshop, SLSFS 2005Bohinj, Slovenia, February 23-25, 2005 ... Papers (Lecture Notes in Computer Science)

Marko Grobelnik, John Shawe-Taylor, Steve R. Gunn, 2006 .

Voted Spheres: An Online, Fast Approach to Large Scale Learning

Craig Saunders, Bassam Farran, 2009, 2009 International Conference on Advanced Information Networking and Applications Workshops.

Exploitation of Machine Learning Techniques in Modelling Phrase Movements for Machine Translation

Mahesan Niranjan, Sándor Szedmák, Craig Saunders, 2011, J. Mach. Learn. Res..

Kernel methods for fMRI pattern prediction

John Ashburner, Craig Saunders, Yizhao Ni, 2008, 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence).

Machine-Learning Applications of Algorithmic Randomness

Alexander Gammerman, Vladimir Vovk, Craig Saunders, 1999, ICML.

Special issue on neural networks and kernel methods for structured domains

Alessandro Sperduti, Barbara Hammer, Craig Saunders, 2005, Neural Networks.

Building look & feel concept models from color combinations

Gabriela Csurka, Craig Saunders, Luca Marchesotti, 2011, The Visual Computer.

Description and evaluation of techniques for transfer learning across sub-categories

Jorma Laaksonen, Kitsuchart Pasupa, Gabriela Csurka, 2009 .

Computationally Efficient Transductive Machines

Alexander Gammerman, Vladimir Vovk, Craig Saunders, 2000, ALT.

Prediction of relevance of an image from a scan pattern

Kitsuchart Pasupa, Samuel Kaski, Arto Klami, 2008 .

Subspace, Latent Structure and Feature Selection, Statistical and Optimization, Perspectives Workshop, SLSFS 2005, Bohinj, Slovenia, February 23-25, 2005, Revised Selected Papers

Marko Grobelnik, John Shawe-Taylor, Steve R. Gunn, 2006, SLSFS.

Learning hierarchical multi-category text classification models

Juho Rousu, John Shawe-Taylor, Sándor Szedmák, 2005, ICML.

Classification using String Kernels

Nello Cristianini, John Shawe-Taylor, Chris Watkins, 2000 .

Kernel-Based Learning of Hierarchical Multilabel Classification Models

Juho Rousu, John Shawe-Taylor, Sándor Szedmák, 2006, J. Mach. Learn. Res..

Analysis of Building Drainage and Sewer System Performance Utilising a Tipping Tank With Water-conserving Measures

David Campbell, Craig Saunders, Sean Mushin, 2016 .

Can relevance of images be inferred from eye movements?

Samuel Kaski, Arto Klami, Craig Saunders, 2008, MIR '08.

Comparing the Bayes and Typicalness Frameworks

Vladimir Vovk, Ilia Nouretdinov, Craig Saunders, 2001, ECML.

Transduction with Confidence and Credibility

Alexander Gammerman, Vladimir Vovk, Craig Saunders, 1999, IJCAI.

A Correlation Approach for Automatic Image Annotation

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

Large scale maximum margin regression based, structural learning approach to phrase translations

Esther Galbrun, Craig Saunders, Sandor Szedmak, 2009, EAMT.

Syllables and other String Kernel Extensions

John Shawe-Taylor, Craig Saunders, Hauke Tschach, 2002, ICML.

Green ICT Resource Set - INFO2009 Coursework, Bobs' Finest Group

Craig Saunders, Pratik Patel, Charalampos Ignatiou, 2010 .

Basic metric learning

John Shawe-Taylor, Kitsuchart Pasupa, Craig Saunders, 2008 .

On Maximum Margin Hierarchical Classification

Juho Rousu, John Shawe-Taylor, Craig Saunders, 2004 .

Kernels and Support Vector Machines

Nello Cristianini, Bernhard Schölkopf, John Shawe-Taylor, 2002 .

Efficient Algorithms for Max-Margin Structured Classification

Juho Rousu, John Shawe-Taylor, Craig Saunders, 2007 .