Previous Graduate Lectures:
HILARY TERM 2018
Date: Thursday 22nd February, 3.30 pm, Small Lecture Theatre, Department of Statistics
Speaker: Jessie Wu, Department of Statistics, University of Oxford
Title: Dirichlet process models and their applications
Abstract: This is an introductory lecture to Dirichlet Processes (DP). The beginning of the lecture will introduce the definition and the various representations of DP to demonstrate how the process can be constructed. Popular variations of DP will also be presented along with the applications of these models, such as clustering and nonparametric regression.
Date: Thursday 15th February, 3.30 pm, Small Lecture Theatre, Department of Statistics
Speaker: Ben Bloem-Reddy, Department of Statistics, University of Oxford
Title: An introduction to exchangeable random partitions and random discrete probability measures
Abstract: Random partition processes underly many constructions for Bayesian models of clustered data; the Chinese Restaurant Process (CRP) is the prototypical example. They are also perhaps the simplest type of combinatorial stochastic process, and are a starting point for studying processes with more complex structure. In the first part of the lecture, I will give an introduction to exchangeable random partitions and their connection to random discrete probability measures via Kingman’s paintbox, with special focus on the CRP. In the second part, I will focus on the properties of the Dirichlet Process (DP), and how different constructions of the DP lead to various classes of random probability measures that appear in the probability and Bayesian nonparametrics literature. Some of these properties will be used in the subsequent week’s grad lecture by Jessie Wu on applications of and inference with models that use the DP as a building block.
Date: Thursday 8th February, 3.30 pm, Small Lecture Theatre, Department of Statistics
Speaker: Marco Scutari, Department of Statistics, University of Oxford
Title: What is new in R?
Abstract: The capabilities of R have evolved considerably since its first public releases in the 1990s, with each major version bringing in new functionality. In this lecture I will discuss two areas which have seen major evolutions in R 3.x.y: the inclusion in the core distribution of the “parallel” package , which provides facilities for parallel computing; and the release of the Hadleyverse packages, which streamline common data cleaning tasks.
Date: Thursday 1st February, 3.30 pm, Small lecture theatre, Department of Statistics
Speaker: Jotun Hein, Department of Statistics, University of Oxford
Title: Statistical Alignment with Long Insertion-Deletions for 2 and More Sequences
Date: Thursday 18th January, 3.30 pm, Small lecture theatre, Department of Statistics
Speaker: Mareli Grady, Department of Statistics
Title: Hands-On Statistics: Getting started in Outreach and Public Engagement
Abstract: The benefits of engaging in outreach and public engagement are numerous and the impacts important. In this talk we will explore the opportunities available in the Department and at Oxford in general, show some examples of outreach and public engagement activities currently in use and give you the opportunity to design and discuss some ideas for yourself. Put your creative hat on and join in!
MICHAELMAS TERM 2017:
Date: Thursday 16th November, 3.30pm
Speaker: Jen Rogers, Department of Statistics, University of Oxford
Abstract: Jen took on the role of Director of Statistical Consultancy Services within the Department in July last year. In this talk she will be presenting her experiences of the job, talking about what is like to work with industry on a consultancy basis and professional aspects associated with the role. She will go through case studies of work that she has carried out, introducing the kinds of statistical problems that she typically encounters. Finally, she will also be outlining ways in which you may be able to get involved with consultancy activities within the Department.
Date: Thursday 2nd November, 3.30pm
Speaker: Dr Ricardo Silva, Lecturer in Statistics, UCL
Abstract: In this exposition, we will discuss the common tools used in the machine learning community to describe causal assumptions and how this leads to particular ways of thinking concerning the estimation of causal effects. We will focus on two main case studies: how to combine data from observational and experimental studies; and how to criticise ways of adjusting for confounding in observational studies, given that background knowledge my be imperfect and hide default assumptions with unintended consequences.
Date: Friday 27th October, 12.00 noon
Abstract: XTX Markets trades an average of $80B daily in thousands of financial instruments on an electronic basis with little human interaction. This adds liquidity to the global financial markets and is made possible by taking a highly systematic, purely data-driven, approach to trading. In this talk, we will describe how trading can be automated, the sort of problems that it poses, and how a small team of mathematicians, statisticians and computer scientists tackles them.
Graduate Talk by XTX Markets followed by pizza lunch.
Date: Thursday 19th October, 3.30 pm
Speaker: Geoff Nicholls, Department of Statistics, University of Oxford
Title: The Savage Axioms for Dummies
Abstract: In Bayesian inference the subjective expected utility is an object of foundational importance. The decision maker’s choices maximise this utility, and so it decides some elements of our statistical methodology.
For the SEU to exist we need a prior and a utility representing the subjective beliefs of the analyst to exist.
The Savage Axioms are a set of axioms which impose a certain “consistency” on our beliefs and values, and are sufficient for a representative prior and utility function to exist. I will present the axioms in the form given by Maurice de Groot,and look at two famous paradoxes which show, or appear to show, that some very natural human beliefs and values are in conflict with these axioms.I will mention some approaches to resolving of these paradoxes and conclude with a brief evaluation of the axioms.
Date: Thursday 12th October, 3.30 pm
Speakers: Professor Charlotte Deane and Professor Gesine Reinert, Department of Statistics, University of Oxford
Title: Active and Passive Presentations: how to present your work, and how to get the most out of seminars, lectures and poster sessions.