Chris Williams
Chris Williams
Professor of Machine Learning, University of Edinburgh
Verified email at inf.ed.ac.uk
Title
Cited by
Cited by
Year
Gaussian processes for machine learning
CE Rasmussen, CKI Williams
MIT Press, 2006
228552006
Gaussian process for machine learning
CE Rasmussen, CKI Williams
MIT press, 2006
215012006
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
108192010
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
34222015
The PASCAL visual object classes challenge 2007 (VOC2007) results
M Everingham, L Van Gool, CKI Williams, J Winn, A Zisserman
27002007
Using the Nyström method to speed up kernel machines
C Williams, M Seeger
Proceedings of the 14th annual conference on neural information processing …, 2001
23152001
GTM: The generative topographic mapping
CM Bishop, M Svensén, CKI Williams
Neural computation 10 (1), 215-234, 1998
17201998
Gaussian processes for regression
CKI Williams, CE Rasmussen
MIT, 1996
12671996
Multi-task Gaussian process prediction
C Williams, EV Bonilla, KM Chai
Advances in neural information processing systems, 153-160, 2007
9472007
Bayesian classification with Gaussian processes
CKI Williams, D Barber
IEEE Transactions on Pattern Analysis and Machine Intelligence 20 (12), 1342 …, 1998
8551998
Prediction with Gaussian processes: From linear regression to linear prediction and beyond
CKI Williams
Learning in graphical models, 599-621, 1998
7771998
Fast forward selection to speed up sparse Gaussian process regression
M Seeger, C Williams, N Lawrence
Artificial Intelligence and Statistics 9, 2003
4982003
Using machine learning to focus iterative optimization
F Agakov, E Bonilla, J Cavazos, B Franke, G Fursin, MFP O'Boyle, ...
International Symposium on Code Generation and Optimization (CGO'06), 11 pp.-305, 2006
4692006
Regression with input-dependent noise: A Gaussian process treatment
PW Goldberg, CKI Williams, CM Bishop
Advances in neural information processing systems 10, 493-499, 1997
3251997
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
2982005
Resin infusion under flexible tooling (RIFT): a review
C Williams, J Summerscales, S Grove
Composites Part A: Applied Science and Manufacturing 27 (7), 517-524, 1996
2701996
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
2682006
Milepost gcc: Machine learning enabled self-tuning compiler
G Fursin, Y Kashnikov, AW Memon, Z Chamski, O Temam, M Namolaru, ...
International journal of parallel programming 39 (3), 296-327, 2011
2402011
Using generative models for handwritten digit recognition
M Revow, CKI Williams, GE Hinton
IEEE transactions on pattern analysis and machine intelligence 18 (6), 592-606, 1996
2351996
GTM: A principled alternative to the self-organizing map
CM Bishop, M Svensén, CKI Williams
International Conference on Artificial Neural Networks, 165-170, 1996
2331996
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