Dr Anthony Lee
Course Director, BSc Data Science degree.
Member, Warwick Data Science Institute.
Associate Member, Oxford-Man Institute of Quantitative Finance.
Associate Editor, Statistics and Computing.
I co-organize Algorithms & Computationally Intensive Inference, an informal reading/discussion group.
From 2011--2013, I was a CRiSM Research Fellow at the University of Warwick.
If you are interested in links between machine learning and computational statistics in the UK, please check out the Network on Computational Statistics and Machine Learning. There is currently a call for collaborative PDRA project proposals.
I am Course Director for the BSc Data Science degree.
2013/14: ST340: Programming for Data Science with Ben Graham.
2012/13: ST414: Advanced Topics in Statistics.
During term these are in C0.16 on
Wednesday: 4.30pm--5.30pm, and
Outside of term, please email me at anthony.lee [at] warwick.ac.uk to arrange an appointment. If you need to speak to me urgently or are unable to make one of these times for any reason then please email me and I will try to make alternative arrangements.
Personal tutees: please book a time to see me on Thursday, 23rd April or come to my office hours.
Monte Carlo Methodology
F. J. Medina-Aguayo, A. Lee, G. O. Roberts. Stability of noisy Metropolis-Hastings.
M. Banterle, C. Grazian, A. Lee, C. P. Robert. Accelerating Metropolis-Hastings algorithms by delayed acceptance.
N. Whiteley, A. Lee. Perfect sampling for nonhomogeneous Markov chains and hidden Markov models.
A. Lee, A. Doucet, K. Łatuszyński. Perfect simulation using atomic regeneration with application to Sequential Monte Carlo.
A. Lee, N. Whiteley. Forest resampling for distributed sequential Monte Carlo.
C. Drovandi, A. N. Pettitt, A. Lee. Bayesian indirect inference using a parametric auxiliary model. Statistical Science 30(1), 2015. [arXiv]
C. Andrieu, A. Lee & M. Vihola. Uniform ergodicity of the iterated conditional SMC and geometric ergodicity of particle Gibbs samplers.
N. Whiteley, A. Lee & K. Heine. On the role of interaction in sequential Monte Carlo algorithms. Bernoulli, to appear. [arXiv 1309.2918]
A. Jasra, A. Lee, C. Yau & X. Zhang. The alive particle filter.
A. Lee & K. Łatuszyński. Variance bounding and geometric ergodicity of Markov chain Monte Carlo kernels for approximate Bayesian computation. Supplementary material. Biometrika 101(3), 2014. [arXiv 1210.6703]
L. M. Murray, A. Lee & P. E. Jacob. Parallel resampling in the particle filter.
P. Del Moral, P. E. Jacob, A. Lee, L. Murray & G. W. Peters. Feynman-Kac particle integration with geometric interacting jumps. Stochastic Analysis and Applications 31(5), 2013 [arXiv 1211.7191].
B. C. May, N. Korda, A. Lee & D. Leslie. Optimistic Bayesian sampling in contextual-bandit problems. JMLR 13(Jun) 2012.
A. Lee, C. Andrieu & A. Doucet. Two discussions of Constructing summary statistics for approximate Bayesian computation: semi-automatic approximate Bayesian computation by P. Fearnhead and D. Prangle. JRSS B 74(3), 2012.
A. Lee, F. Caron, A. Doucet & C. Holmes. Bayesian sparsity-path-analysis of genetic association signal using generalized t priors. Statistical Applications in Genetics and Molecular Biology 11(2), 2012 [arXiv 1106.0322].
A. Lee, F. Caron, A. Doucet & C. Holmes. A hierarchical Bayesian framework for constructing sparsity-inducing priors.
A. Lee, C. Yau, M. Giles, A. Doucet & C. Holmes. On the utility of graphics cards to perform massively parallel simulation of advanced Monte Carlo methods. JCGS 19(4), 2010 [arXiv 0905.2441]. Related Website.
A. Lee & C. Holmes. Discussion of Particle Markov chain Monte Carlo methods by C. Andrieu, A. Doucet and R. Holenstein. JRSS B 72(3), 2010.
A. Lee. Towards smooth particle filters for likelihood estimation with multivariate latent variables. M.Sc. Thesis, UBC, 2008.
08/15: SMC 2015 Workshop, Paris.
02/15: Machine Learning Seminar, Gatsby Computational Neuroscience Unit.
02/15: Statistics Seminar, Imperial College London.
04/14: Advanced Monte Carlo Methods for Complex Inference Problems, Isaac Newton Institute, Cambridge.
03/14: i-like Workshop, University of Oxford.
03/14: Applied Mathematics Seminar, University of Leicester.
03/14: Advances in Scalable Bayesian Computation, BIRS workshop, Banff.
01/14: Statistics Seminar, Newcastle University.
01/14: Statistics Seminar, University of Cambridge.
01/14: MCMSki IV, Chamonix.
09/13: RSS Int'l Conference 2013, Newcastle.
08/13: Joint Statistical Meeting 2013, Montreal.
07/13: European Meeting of Statisticians, Budapest.
05/13: ABC in Rome.
04/13: Compstats Talk, Lancaster University.
01/13: Statistics Seminar, National University of Singapore.
12/12: Winter Simulation Conference 2012, Berlin.
12/12: ERCIM 2012, Oviedo.
10/12: Statistics Seminar, University of Glasgow.
09/12: RSS Int'l Conference 2012, Telford.
07/12: CMIS Seminar, Perth.
06/12: ISBA 2012, Kyoto.
04/12: Statistics Seminar, University of Bristol.
04/12: Confronting Intractability in Statistical Inference, University of Bristol.
03/12: Statistics Seminar, University of Kent.
02/12: OeRC GPU Seminar, Unviersity of Oxford.
02/12: Recent Advances in Monte Carlo Methods, Royal Statistical Society.
01/12: Introduction, GPUs in Computational Statistics, University of Warwick.
08/11: JSM 2011, Miami.
06/11: Statistics Seminar, Imperial College London.
06/11: Greek Stochastics Meeting, Crete.
03/11: Monte Carlo Methods Workshop, University of Warwick.
08/10: Greek Stochastics Meeting, Lefkada.
06/10: Valencia 9, Benidorm (with Chris Holmes).
02/10: SIAM PP10, Seattle.
11/09: Signal Processing Seminar, University of Cambridge.
08/09: Greek Stochastics Meeting, Lefkada (Best Contributed Talk Award).
Department of Statistics
University of Warwick
Coventry CV4 7AL
Phone: +44 2476 150042
Fax: +44 2476 524532
anthony.lee [at] warwick.ac.uk
D. Phil. (2011)
University of Oxford
M. Sc. (2008)
University of British Columbia
B. Sc. (2006)
University of British Columbia