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Algorithms & Computationally Intensive Inference seminars

2020/2021: The seminars will happen on Microsoft Teams on Fridays 1pm UK time (or occasionally at different times).

If you are not affiliated with Warwick and wish to attend our seminars please register here.

If you would like to speak, or you want to be included in any emails, please contact one of the organisers.

Current Organisers: Massimiliano Tamborrino, Jure Vogrinc

Website URL: www.warwick.ac.uk/compstat

Mailing List Sign-Up: http://mailman1.csv.warwick.ac.uk/mailman/listinfo/algorithmseminar

Mailing List: algorithmseminar@listserv.csv.warwick.ac.uk (NB - only approved members can post)

Microsoft Teams Link (username/password same as for eduroam) available here

Next talk, Friday 22/1 at 4pm UK time:

Jeffrey Rosenthal: MCMC Confidence Intervals and Biases Without CLTs

This week will exceptionally happen on zoom. Pass: 450131

Abstract: Most estimates of MCMC errors rely on versions of the Markov chain Central Limit Theorem (CLT), which might not always hold and can be difficult to verify. I will discuss an alternative approach using just Chebychev’s inequality together with basic variance estimates, which provides slightly larger confidence intervals (2.3 times as wide) without requiring any CLT. This approach in turn raises questions about bounds on MCMC bias and its relation to Markov chain convergence rates.

2020/21 Term 2:

Date Speaker Title Abstract Slides Video
Week 1: 15/1 (4pm UK time) Jeremias Knoblauch Postponed to 12/2 at 4pm Abstract    
Week 2: 22/1 (4pm UK time) Jeffrey Rosenthal MCMC Confidence Intervals and Biases Without CLTs Abstract    
Week 3: 29/1 Paul Dobson        
Week 4: 5/2 Daniel Jerison        
Week 5: 12/2 Jaromir Sant        
Week 5: 12/2
(4pm UK time)
Jeremias Knoblauch Optimization-centric Generalizations of Bayesian Inference Abstract    
Week 6: 19/2 Xenia Miscouridou        
Week 7: 26/2 Nianqiao (Phyllis) Ju        
Week 8: 5/3 Adeline Samson        
Week 9: 12/3 (4 pm UK time) Ari Stern        
Week 10: 19/3 TBA        
2020/21 Term 3:
Date Speaker Title Abstract Slides Video
Week 1: 30/4 TBA        
Week 2: 7/5 TBA        
Week 3: 14/5 TBA        
Week 4: 21/5 TBA        
Week 5: 28/5 TBA        
Week 6: 4/6 TBA        
Week 7: 11/6 TBA        
Week 8: 18/6 TBA        
Week 9: 25/6 TBA        
Week 10: 2/7 TBA        
2020/21 Term 1 (and September)

This is the list of confirmed speakers, which will be continuously updated.

Date Speaker Title Abstract Slides Video
Week -2: 18/09 (12 UK time) Clara Grazian Approximate Bayesian analysis of (un)conditional copulas Abstract Slides Video
Week -1: 25/09 Joe Meagher Bayesian Ancestral Reconstruction for Bat Echolocation Abstract Slides Video
Week0: 02/10 Michael Choi On the convergence of an improved and adaptive kinetic simulated annealing Abstract Slides Video
Week 1: 09/10   cancelled (OxWaSP workshop)      
Week 2: 16/10 (2pm UK time) Liangliang Wang Sequential Monte Carlo for estimating parameters of differential equations Abstract Slides Video
Week 3: 23/10 Sebastian Vollmer

Part 1: Risk prediction and Risk prediction

Part 2: Machine Learning in Julia and benchmarking results on predictive fairness.

Abstract   Video
Week 4: 30/10 (4pm UK time) Philippe Gagnon Lifted samplers for partially ordered discrete state-spaces Abstract   Video
Week 5: 6/11 Richard Everitt

Rare event ABC-SMC^2

Abstract Slides Video
Week 6: 13/11 Letizia Angeli Interacting Particle Systems Approximations of Feynman-Kac Formulae in continuous time Abstract Slides Video
Week 7: 20/11 Yan Qu Exact Simulation of Self-Excited Point Process with Levy Driven OU Abstract    
Week 8: 27/11
(4pm UK time)
Caroline Colijn
COVID-19 data sources and their challenges for modelling and estimation
Abstract    
Week 9: 4/12 Suzie Brown Asymptotic genealogies of sequential Monte Carlo algorithms Abstract    
Week 10: 11/12   cancelled      

Previous Years:

2019/2020

2018/2019

2017/2018

2016/2017

2015/2016

2014/2015

2013/2014

2012/2013

2011/2012 

2010/2011

Some key phrases:

- Sampling and inference for diffusions
- Exact algorithms
- Intractable likelihood
- Pseudo-marginal algorithms
- Particle filters
- Importance sampling
- MCMC
- Adaptive MCMC
- Perfect simulation
- Markov chains
- Random structures
- Randomised algorithms