Kernel
Methods for Pattern Analysis
(John Shawe-Taylor and Nello Cristianini);
Cambridge University Press; 2004
(www.kernel-methods.net)
(+ Chinese Edition, 2005)
Introduction
to Computational Genomics
(Nello Cristianini and Matthew Hahn)
Cambridge University Press; 2006
(www.computational-genomics.net)
2007
A
Kernel Canonical Correlation Analysis for Learning the Semantics
of Text,
B. Fortuna, N. Cristianini, and J. Shawe-Taylor,
Kernel Methods in Bioengineering, Signal and Image Processing,
edited by Dr. Gustavo Camps-Valls, Dr. Jose Luis Rojo-Alvarez, and
Dr. Manel Martinez-Ramon [to appear]
Kernel Methods,
N. Cristianini, J. Shawe-Taylor, and C. Saunders,Kernel Methods
in Bioengineering, Signal and Image Processing,
edited by Dr. Gustavo Camps-Valls, Dr. Jose Luis Rojo-Alvarez, and
Dr. Manel Martinez-Ramon, [to appear]
2006
On Kernel Target Alignment
Nello Cristianini, Jaz Kandola, Andre Elisseeff and John
Shawe-Taylor
In "Innovations in Machine Learning: Theory and Application"s
Editors: Dawn Holmes, Lakhmi Jain; ISBN: 3-540-30609-9
Springer Verlag, 2006 [PS][older
version]
The
Evolution of Mammalian Gene Families
(Demuth JP, Bie TD, Stajich JE, Cristianini N, Hahn MW.)
PLoS ONE. 2006 Dec 20;1(1):e85.
Fast SDP Relaxations of Graph Cut Clustering, Transduction,
and Other Combinatorial Problems
Tijl De Bie and Nello Cristianini,
Journal of Machine Learning Research, 7(Jul):1409--1436, 2006.
CAFE: a computational tool for the study of gene
family evolution
Tijl De Bie, Nello Cristianini, Jeffery P. Demuth, and Matthew W.
H
Bioinformatics 2006 22(10):1269-1271; doi:10.1093/bioinformatics/btl097
Modeling Sequence Evolution with Kernel Methods
M. Bresco, M. Turchi, T. De Bie, N. Cristianini
Computational Optimization and Applications – In Press
2005
On
the Eigenspectrum of the Gram matrix and the generalization error
of kernel PCA (John Shawe-Taylor, Chris Williams, Nello
Cristianini, Jaz S. Kandola) IEEE Tranactions on Information Theory
51(7) 2510-2522 (2005)
Estimating
the tempo and mode of gene family evolution from comparative genomic
data
M. Hahn, T. de Bie, C. Nguyen, J. Stajich, N. Cristianini
Genome Research 15:1153-1160, 2005
Eigenproblems in Pattern Recognition, (De Bie T., Cristianini
N., Rosipal R.,) “Handbook of Computational Geometry for Pattern
Recognition, Computer Vision, Neurocomputing and Robotics”,
E. Bayro-Corrochano (editor), Springer-Verlag, 2005
Discovering regulatory modules from heterogeneous information sources, De Bie T., Monsieurs P., Engelen K., De Moor B., Cristianini N., Marchal K., To Appear: Proceedings of the Pacific Symposium on Biocomputing (PSB). , 2005
2004
Kernel-based Integration of Genomic Data using Semidefinite Programming . (Lanckriet, G.R.G., Cristianini, N., Jordan, M.I., Noble, W.S.) In B. Schoelkopf, K. Tsuda and J.-P. Vert (Eds.), Kernel Methods in Computational Biology: MIT Press. (2004)
A
Statistical Framework for Genomic Data Fusion, (Lanckriet
G., De Bie T., Cristianini N., Jordan M., Stafford Noble W.,) Bioinformatics
(to appear: advance access published on May 6, 2004, DOI 10.1093/bioinformatics/bth294).
(2004)
Learning the Kernel Matrix with Semidefinite Programming.
(Lanckriet, G.R.G., Cristianini, N., Bartlett, P., El Ghaoui, L.,
Jordan, M.I.) Journal of Machine Learning Research, 5, 27-72, 2004.
(2004).
Kernel-based Data Fusion and its Application to
Protein Function Prediction in Yeast . (Lanckriet, G.R.G.,
Deng, M., Cristianini, N. , Jordan, M.I., Noble, W.S.) Proceedings
of the Pacific Symposium on Biocomputing (PSB). , 2004
Kernel methods for exploratory data analysis: a demonstration on text data, (De Bie T., Cristianini N.,) in: Structural, Syntactic, and Statistical Pattern Recognition, Proc. Joint IAPR International Workshops SSPR 2004 and SPR 2004 (Lisbon, Portugal, August 18-20, 2004), Lecture Notes in Computer Science, 3139, Springer Verlag, Berlin, 2004.
2003
Convex
Methods for Transduction, (De Bie T., Cristianini N.,)
Neural Information Processing Systems (NIPS2003), Vancouver, Canada,
December 2003.
Efficiently Learning the Metric using Side-Information, (De Bie T., Momma M., Cristianini N.,) in Proc. of the 14th International Conference on Algorithmic Learning Theory (ALT2003), Sapporo, Japan, Lecture Notes in Artificial Intelligence, Vol. 2842, pp. 175-189, Springer, 2003.
2002
Kernel
Methods: Current Research and Future Directions Nello Cristianini,
Colin Campbell, Chris Burges, Machine Learning 46(1/3): 5-9, January
2002
Support Vector Machines and Kernel Methods, The
New Generation of Learning Machines (Nello Cristianini,
Bernhard Schoelkopf)
Artificial Intelligence Magazine, Volume 23, No 3 pg 31-41
Latent Semantic Kernels (Nello Cristianini, Huma Lodhi, John Shawe-Taylor) Journal of Intelligent Information Systems (JJIS) Vol. 18, No. 2 (March 2002) [PS]
String Matching Kernels for Text Classification,
(Huma Lodhi, Craig Saunders, John Shawe-Taylor, Nello Cristianini,
Chris Watkins) Journal of Machine Learning Research, 2(Feb):419-444,
2002 [PS]
On the Generalisation of Soft Margin Algorithms
(Shawe-Taylor, J. and Cristianini, N., IEEE Transactions
on Information Theory 48(10):pp. 2721-2735. (2002) [PS]
On the
Eigenspectrum of the Gram Matrix and Its Relationship to the Operator
Eigenspectrum.
(John Shawe-Taylor, Chris Williams, Nello Cristianini, Jaz S. Kandola)
-- ALT 2002: 23-40 [PDF]
Learning
Semantic Similarity
(Jaz Kandola, Nello Cristianini, John Shawe-Taylor)
NIPS 2002 [PS]
Inferring
a Semantic Representation of Text via Cross-Language Correlation
Analysis
(Alexei Vinokourov, Nello Cristianini, John Shawe-Taylor)
NIPS 2002 [PDF]
Learning
The Kernel Matrix with Semi-Definite Programming
(Gert Lanckriet, Nello Cristianini, Peter Bartlett, Laurent El Gahoui,
Michael Jordan)
ICML 2002 [PDF]
2001
Discrete Kernels for Text Categorisation (Huma Lodhi, John Shawe-Taylor, Nello Cristianini, Chris Watkins) (In Advances in Neural Information Processing Systems (NIPS), vol. 13. (2001) [PS]
On Kernel-Target
Alignment,
(Nello Cristianini, John Shawe-Taylor, Andre Elisseeff, Jaz Kandola),
NIPS 2001 [PS]
Spectral
Kernel Methods for Clustering
(Nello Cristianini, John Shawe-Taylor, Jaz Kandola)
NIPS 2001 [PS]
On the Concentration
of Spectral Properties
(John Shawe-Taylor, Nello Cristianini, Jaz Kandola) NIPS 2001 [PS]
Latent Semantic
Kernels
(Nello Cristianini, Huma Lodhi, John Shawe-Taylor)
ICML2001
Combination
Kernels for Hypertext
(Thorsten Joachims, Nello Cristianini and John Shawe-Taylor),
ICML2001 [PDF]
2000
Enlarging the Margin in Perceptron Decision Trees; (Kristin Bennett; Nello Cristianini; John Shawe-Taylor; Donghui Wu; ); Machine Learning 41(3): 295-313, December 2000 [PDF]
Support Vector Machine Classification of Microarray
Gene Expression Data (Michael P. S. Brown, William Noble
Grundy, David Lin, Nello Cristianini, Charles Sugnet, Manuel Ares,
Jr., David Haussler); PNAS -.Proc. Natl. Acad. Sci. USA, vol. 97,
pages 262-267 (2000) [PDF]
Support Vector Machine Classification and Validation
of Cancer Tissue Samples Using Microarray Expression Data (Terry
Furey, Nello Cristianini, Nigel Duffy, Michel Schummer, David Bednarski,
David Haussler) Bioinformatics, 16(10): 906-914 (2000) [PDF]
Large Margin
DAGs for Multiclass Classification;
(John Platt; Nello Cristianini; John Shawe-Taylor).
In Advances in Neural Information Processing Systems (NIPS),
vol. 12. (2000) [PS]
Query Strategies
for Large Margin Cassifiers
(Colin Campbell, Nello Cristianini, Alex Smola)
In Proceedings of the Seventeenth International Conference on Machine
Learning, (ICML 2000) [PS]
1999
Large Margin Classifiers and Bayesian Voting Schemes (Nello Cristianini and John Shawe-Taylor ) in: Advances in Kernel Methods - Support Vector Learning}, 1999, MIT Press (Chapter 5, pg.55-68); ed. by B. Schoelkopf, C. Burges, A. Smola [PS]
Soft Margin and Margin Distribution; (John
Shawe-Taylor and Nello Cristianini); in: Advances in Large Margin
Classifiers; ed. by A. Smola; B. Schoelkopf; P. Bartlett; D. Schuurmans.
MIT Press – 1999 [PS]
Dynamically Adapting Kernels in Support Vector Machines;
(Nello Cristianini; Colin Campbell; John Shawe-Taylor)
in: Kearns M., Solla S., Cohn D., editors; Advances in Neural Information
Processing Systems (NIPS) vol. 11, 1999, MIT Press [PS]
Multiplicative
Updatings for Support Vector Learning
(Nello Cristianini; Colin Campbell; John Shawe-Taylor)
in: Proceedings of: European Symposium on Artificial Neural Networks
(ESANN) 1999
Margin Distribution
Bounds on Generalization
(John Shawe-Taylor; Nello Cristianini)
in: Proceedings of European Conference on Computational learning
Theory, (EuroColt) 1999 [PS]
Large Margin
Decision Trees for Induction and Transduction;
(Donghui Wu, Kristin Bennett; Nello Cristianini; John Shawe-Taylor;)
In Proceedings of the Sixteenth International Conference on Machine
Learning, (ICML)1999
Further
Results on the Margin Distribution;
(John Shawe-Taylor; Nello Cristianini);
In Proceedings of Conference on Computational Learning Theory (COLT),
1999 [PS]
Controlling
the Sensitivity of Support Vector Machines;
(Kostas Veropoulos; Colin Campbell; Nello Cristianini);
proceeding of SVM workshop at IJCAI 1999 [PS]
Diagnosis
of TBC with Support Vector Machines
(Kostas Veropoulos, Nello Cristianini, Colin Campbell)
in Proceedings of ACAI '99 (Chania, Crete 1999)
1998
Large Margin
Classification Using the Kernel Adatron Algorithm
(Colin Campbell; Thilo Friess; Nello Cristianini);
In Proceedings of: IDEAL 98
Data Dependent
Structural Risk Minimization for Perceptron Decision Trees
(John Shawe-Taylor; Nello Cristianini)
in: Jordan M.,
Bayesian
Classifiers are Large Margin Hyperplanes in a Hilbert Space;
(Nello Cristianini; John Shawe-Taylor; Peter Sykacek)
in: Shavlik, J. (ed) Proceeding of the Fifteenth International Conference
on Machine Learning (ICML), 1998,
pg.109-117, and (extended version) submitted to Machine Learning
Journal [PS]
The Kernel-Adatron:
a Fast and Simple Learning Procedure for Support Vector Machines
(Thilo Friess; Nello Cristianini; Colin Campbell;)
in: Shavlik, J. (ed) Proceeding of the Fifteenth International Conference
on Machine Learning (ICML),1998, pg. 188-196