Course Director, BSc Data Science degree.
Faculty Fellow, Alan Turing Institute.
Strategic Programme Director, Intel--Turing Partnership.
Member, Warwick Data Science Institute.
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.
I am Course Director for the BSc Data Science degree.
2015/16: ST912: Statistical Frontiers
2012/13: ST414: Advanced Topics in Statistics.
During term these are in C0.16 on
I am away the week of 20th February. Personal tutees: if you urgently need to see a faculty member, please arrange an appointment to meet with Dr. Adam Johansen.
It is a good idea to let me know by email if you plan to attend a particular office hour.
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.
Monte Carlo methodology
Parallel and distributed algorithms
Scalable data analysis
Lawrence Middleton (OxWaSP, based in Oxford). Co-supervised with Arnaud Doucet.
L. M. Murray, S. Singh, P. E. Jacob, A. Lee. Anytime Monte Carlo.
C. Sherlock, A. H. Thiery, A. Lee. Pseudo-marginal Metropolis-Hastings using averages of unbiased estimators.
G. Deligiannidis, A. Lee. Which ergodic averages have finite asymptotic variance?
L. F. Price, C. C. Drovandi, A. Lee, D. J. Nott. Bayesian synthetic likelihood. Journal of Computational and Graphical Statistics, to appear.
F. J. Medina-Aguayo, A. Lee, G. O. Roberts. Stability of noisy Metropolis-Hastings. Statistics and Computing 26(6), 2016.
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. Annals of Applied Probability 26(5), 2016. [arXiv 1410.4462]
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. Statistical Analysis and Data Mining 9(4), 2016. [preprint]
C. Drovandi, A. N. Pettitt, A. Lee. Bayesian indirect inference using a parametric auxiliary model. Statistical Science 30(1), 2015. [arXiv 1505.03372]
C. Andrieu, A. Lee & M. Vihola. Uniform ergodicity of the iterated conditional SMC and geometric ergodicity of particle Gibbs samplers. Bernoulli, to appear.
N. Whiteley, A. Lee & K. Heine. On the role of interaction in sequential Monte Carlo algorithms. Bernoulli 22(1), 2016. [arXiv 1309.2918]
P. Del Moral, A. Jasra, A. Lee, C. Yau & X. Zhang. The alive particle filter and its use in particle Markov chain Monte Carlo. Stochastic Analysis and Applications 33(6), 2015. [preprint]
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]
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].
A. Lee. On the choice of MCMC kernels for approximate Bayesian computation with SMC samplers. Winter Simulation Conference, 2012.
B. C. May, N. Korda, A. Lee & D. Leslie. Optimistic Bayesian sampling in contextual-bandit problems. Journal of Machine Learning Research 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. Journal of the Royal Statistical Society 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.Journal of Computational and Graphical Statistics 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.Journal of the Royal Statistical Society B 72(3), 2010.
A. Lee. Towards smooth particle filters for likelihood estimation with multivariate latent variables. M.Sc. Thesis, UBC, 2008.
Seminars / Workshops / Conferences
07/17: Scalable Inference, Isaac Newton Institute, Cambridge.
05/17: Statistics Seminar, University of Bath.
02/17: Validating and expanding approximate Bayesian computation methods, BIRS workshop, Banff.
02/17: HPC and Big Data, London.
01/17: Statistics Seminar, University of York.
01/17: Statistics Seminar, King's College London.
06/16: MCMC and Diffusion Techniques Workshop, Alan Turing Institute.
04/16: SIAM Conference on Uncertainty Quantification, Lausanne.
03/16: Statistics Seminar, University of Bristol.
02/16: Probabilistic Programming Workshop, Alan Turing Institute.
02/16: Probability, stochastic modelling and financial mathematics Seminar, University of Leeds.
01/16: MCMSki 5, Lenzerheide.
12/15: NIPS Workshop on Scalable Monte Carlo for Big Data, Montreal.
08/15: SMC 2015 Workshop, Paris.
06/15: Bayesian Inference for Big Data 2015, University of Oxford.
05/15: Econometrics Workshops, University of Surrey.
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