Colin Campbell
Colin Campbell
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Support vector machines: hype or hallelujah?
KP Bennett, C Campbell
Acm Sigkdd Explorations Newsletter 2 (2), 1-13, 2000
Controlling the sensitivity of support vector machines
K Veropoulos, C Campbell, N Cristianini
Proceedings of the international joint conference on AI 55, 60, 1999
Query learning with large margin classifiers
C Campbell, N Cristianini, A Smola
ICML 20 (0), 0, 2000
The kernel-adatron algorithm: a fast and simple learning procedure for support vector machines
TT Frie, N Cristianini, C Campbell
Machine learning: proceedings of the fifteenth international conference …, 1998
An integrative approach to predicting the functional effects of non-coding and coding sequence variation
HA Shihab, MF Rogers, J Gough, M Mort, DN Cooper, INM Day, TR Gaunt, ...
Bioinformatics 31 (10), 1536-1543, 2015
Kernel methods: a survey of current techniques
C Campbell
Neurocomputing 48 (1-4), 63-84, 2002
Learning with support vector machines
C Campbell, Y Ying
Synthesis lectures on artificial intelligence and machine learning 5 (1), 1-95, 2011
Bayes point machines
R Herbrich, T Graepel, C Campbell
Journal of Machine Learning Research 1 (Aug), 245-279, 2001
Estimating dataset size requirements for classifying DNA microarray data
S Mukherjee, P Tamayo, S Rogers, R Rifkin, A Engle, C Campbell, ...
Journal of computational biology 10 (2), 119-142, 2003
A linear programming approach to novelty detection
C Campbell, KP Bennett
Advances in neural information processing systems, 395-401, 2001
N= 2, D= 10 non-chiral supergravity and its spontaneous compactification
ICG Campbell, PC West
Nuclear Physics B 243 (1), 112-124, 1984
Dynamically adapting kernels in support vector machines
N Cristianini, C Campbell, J Shawe-Taylor
Advances in neural information processing systems, 204-210, 1999
Bayesian automatic relevance determination algorithms for classifying gene expression data
Y Li, C Campbell, M Tipping
Bioinformatics 18 (10), 1332-1339, 2002
An introduction to kernel methods
C Campbell
Studies in Fuzziness and Soft Computing 66, 155-192, 2001
Sparse metric learning via smooth optimization
Y Ying, K Huang, C Campbell
Advances in neural information processing systems, 2214-2222, 2009
Genome-wide screening for complete genetic loss in prostate cancer by comparative hybridization onto cDNA microarrays
J Clark, S Edwards, A Feber, P Flohr, M John, I Giddings, S Crossland, ...
Oncogene 22 (8), 1247-1252, 2003
The latent process decomposition of cDNA microarray data sets
S Rogers, M Girolami, C Campbell, R Breitling
IEEE/ACM transactions on computational biology and bioinformatics 2 (2), 143-156, 2005
Expression analysis onto microarrays of randomly selected cDNA clones highlights HOXB13 as a marker of human prostate cancer
S Edwards, C Campbell, P Flohr, J Shipley, I Giddings, R Te-Poele, ...
British journal of cancer 92 (2), 376-381, 2005
Automated identification of tubercle bacilli in sputum. A preliminary investigation.
K Veropoulos, GĖ Learmonth, C Campbell, B Knight, J Simpson
Analytical and quantitative cytology and histology 21 (4), 277, 1999
Identification of amplified and expressed genes in breast cancer by comparative hybridization onto microarrays of randomly selected cDNA clones
J Clark, S Edwards, M John, P Flohr, T Gordon, K Maillard, I Giddings, ...
Genes, Chromosomes and Cancer 34 (1), 104-114, 2002
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