Chris Williams
Chris Williams
Professor of Machine Learning, University of Edinburgh
Verified email at inf.ed.ac.uk
TitleCited byYear
Gaussian processes for machine learning
CE Rasmussen, CKI Williams
MIT Press, 2006
159242006
Gaussian process for machine learning
CE Rasmussen, CKI Williams
MIT press, 2006
159032006
The PASCAL Visual Object Classes (VOC) challenge
M Everingham, L Van Gool, CKI Williams, J Winn, A Zisserman
Int J Computer Vision 88 (2), 303-338, 2010
70232010
The PASCAL visual object classes challenge 2007 (VOC2007) results
M Everingham, L Van Gool, CKI Williams, J Winn, A Zisserman
22282007
The pascal visual object classes challenge: A retrospective
M Everingham, SMA Eslami, L Van Gool, CKI Williams, J Winn, ...
International journal of computer vision 111 (1), 98-136, 2015
19182015
Using the Nyström method to speed up kernel machines
CKI Williams, M Seeger
Advances in neural information processing systems, 682-688, 2001
19112001
GTM: The generative topographic mapping
CM Bishop, M Svensén, CKI Williams
Neural computation 10 (1), 215-234, 1998
16091998
Gaussian processes for regression
CKI Williams, CE Rasmussen
Advances in neural information processing systems, 514-520, 1996
10301996
Bayesian classification with Gaussian processes
CKI Williams, D Barber
IEEE Transactions on Pattern Analysis and Machine Intelligence 20 (12), 1342 …, 1998
7341998
Multi-task Gaussian process prediction
EV Bonilla, KM Chai, C Williams
Advances in neural information processing systems, 153-160, 2008
6982008
Prediction with Gaussian processes: From linear regression to linear prediction and beyond
CKI Williams
Learning in graphical models, 599-621, 1998
6581998
Gaussian processes for machine learning
CKI Williams, CE Rasmussen
MIT press 2 (3), 4, 2006
5372006
Using machine learning to focus iterative optimization
F Agakov, E Bonilla, J Cavazos, B Franke, G Fursin, MFP O'Boyle, ...
Proceedings of the international symposium on code generation and …, 2006
4132006
Fast forward selection to speed up sparse Gaussian process regression
M Seeger, C Williams, N Lawrence
Artificial Intelligence and Statistics 9, 2003
3932003
Gaussian processes for machine learning, vol. 1
CE Rasmussen, CK Williams
MIT press 39, 40-43, 2006
3172006
Computing with infinite networks
CKI Williams
Advances in neural information processing systems, 295-301, 1997
2931997
The 2005 pascal visual object classes challenge
M Everingham, A Zisserman, CKI Williams, L Van Gool, M Allan, ...
Machine Learning Challenges Workshop, 117-176, 2005
2642005
Pascal visual object classes challenge results
M Everingham, LV Gool, C Williams, A Zisserman
Available from www. pascal-network. org 1 (6), 7, 2005
2612005
Regression with input-dependent noise: A Gaussian process treatment
PW Goldberg, CKI Williams, CM Bishop
Advances in neural information processing systems, 493-499, 1998
2571998
Dataset issues in object recognition
J Ponce, TL Berg, M Everingham, DA Forsyth, M Hebert, S Lazebnik, ...
Toward category-level object recognition, 29-48, 2006
2342006
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