Craig Saunders

2007
16	EE	Craig Saunders, Anthony Demco: Kernels for Strings and Graphs. Perspectives of Neural-Symbolic Integration 2007: 7-22
2006
15		Craig Saunders, Marko Grobelnik, Steve R. Gunn, John Shawe-Taylor: Subspace, Latent Structure and Feature Selection, Statistical and Optimization, Perspectives Workshop, SLSFS 2005, Bohinj, Slovenia, February 23-25, 2005, Revised Selected Papers Springer 2006
14	EE	David R. Hardoon, Craig Saunders, Sándor Szedmák, John Shawe-Taylor: A Correlation Approach for Automatic Image Annotation. ADMA 2006: 681-692
13	EE	Juho Rousu, Craig Saunders, Sándor Szedmák, John Shawe-Taylor: Kernel-Based Learning of Hierarchical Multilabel Classification Models. Journal of Machine Learning Research 7: 1601-1626 (2006)
2005
12	EE	Alexei Vinokourov, Andrei N. Soklakov, Craig Saunders: A probabilistic framework for mismatch and profile string kernels. ESANN 2005: 325-330
11	EE	Juho Rousu, Craig Saunders, Sándor Szedmák, John Shawe-Taylor: Learning hierarchical multi-category text classification models. ICML 2005: 744-751
10	EE	Barbara Hammer, Craig Saunders, Alessandro Sperduti: Special issue on neural networks and kernel methods for structured domains. Neural Networks 18(8): 1015-1018 (2005)
2004
9	EE	Craig Saunders, David R. Hardoon, John Shawe-Taylor, Gerhard Widmer: Using String Kernels to Identify Famous Performers from Their Playing Style. ECML 2004: 384-395
2002
8		Craig Saunders, Hauke Tschach, John Shawe-Taylor: Syllables and other String Kernel Extensions. ICML 2002: 530-537
7	EE	Craig Saunders, John Shawe-Taylor, Alexei Vinokourov: String Kernels, Fisher Kernels and Finite State Automata. NIPS 2002: 633-640
6	EE	Huma Lodhi, Craig Saunders, John Shawe-Taylor, Nello Cristianini, Christopher J. C. H. Watkins: Text Classification using String Kernels. Journal of Machine Learning Research 2: 419-444 (2002)
2001
5	EE	Thomas Melluish, Craig Saunders, Ilia Nouretdinov, Volodya Vovk: Comparing the Bayes and Typicalness Frameworks. ECML 2001: 360-371
2000
4	EE	Craig Saunders, Alexander Gammerman, Volodya Vovk: Computationally Efficient Transductive Machines. ALT 2000: 325-333
1999
3		Volodya Vovk, Alexander Gammerman, Craig Saunders: Machine-Learning Applications of Algorithmic Randomness. ICML 1999: 444-453
2		Craig Saunders, Alexander Gammerman, Volodya Vovk: Transduction with Confidence and Credibility. IJCAI 1999: 722-726
1998
1		Craig Saunders, Alexander Gammerman, Volodya Vovk: Ridge Regression Learning Algorithm in Dual Variables. ICML 1998: 515-521

Coauthor Index

1	Nello Cristianini	[6]
2	Anthony Demco	[16]
3	Alexander Gammerman (Alex J. Gammerman)	[1] [2] [3] [4]
4	Marko Grobelnik	[15]
5	Steve R. Gunn	[15]
6	Barbara Hammer	[10]
7	David R. Hardoon	[9] [14]
8	Huma Lodhi	[6]
9	Thomas Melluish	[5]
10	Ilia Nouretdinov	[5]
11	Juho Rousu	[11] [13]
12	John Shawe-Taylor	[6] [7] [8] [9] [11] [13] [14] [15]
13	Andrei N. Soklakov	[12]
14	Alessandro Sperduti	[10]
15	Sándor Szedmák	[11] [13] [14]
16	Hauke Tschach	[8]
17	Alexei Vinokourov	[7] [12]
18	Vladimir Vovk (Volodya Vovk, V. G. Vovk)	[1] [2] [3] [4] [5]
19	Christopher J. C. H. Watkins	[6]
20	Gerhard Widmer	[9]

Colors in the list of coauthors