Date:09 July 2018, Monday
Location:S16-05-96, Computer Lab 4
Time:02:00pm - 03:00pm
Sequential Monte Carlo Algorithms for High-Dimensional Filtering and SmoothingPHD ORAL PRESENTATION Hidden Markov models are one of the most successful statistical modelling ideas that have been developed…
Date:20 June 2018, Wednesday
Location:S16-06-118, Statistics Seminar Room
Time:03:00pm - 04:00pm
The GUIDE Approach to Missing DataGUIDE is a classification and regression tree algorithm that can be used in many missing data settings. For prediction…
Date:23 May 2018, Wednesday
Location:S17 #04-06 Mathematics Seminar Room 1, Faculty of Science
Time:10:30am - 11:30am
Max-linear Models on GraphsGraphical models are a popular tool to analyse and visualise dependence properties between random variables; see e.g. Lauritzen (1996)….
Date:23 April 2018, Monday
Location:S16-05-96, Computer Lab 4
Time:11:00am - 12:00pm
Multilevel Particle Filters For Continuous Time ProcessesPHD ORAL PRESENTATION In recent times, practical problems of interest such as continuous time processes and its applications have…
Date:18 April 2018, Wednesday
Location:S16-06-118, DSAP Seminar Room
Time:03:00pm - 04:00pm
A Central Limit Theorem for Sequential MCMC MethodsWe present a theoretical analysis of a class of particle filters (PFs), which differ from conventional PFs in the…
Date:11 April 2018, Wednesday
Location:03:00pm - 04:00pm
Time:S16-06-118, DSAP Seminar Room
Customer Churn IntelligenceA Case Study Approach: Retaining customers with high churn risk is one of the toughest challenges in the telecommunication…
Date:04 April 2018, Wednesday
Location:S16-06-118, DSAP Seminar Room
Time:04:00pm - 05:00pm
Principle of Correlation and Feature Selection in High-DimensionalThe intrinsic mechanism of feature selection for linear models is correlation. For instance, invarious sequential methods, the features are…
Date:28 March 2018, Wednesday
Location:S16-06-118, DSAP Seminar Room
Time:02:00pm - 03:00pm
Modeling and Inference of Local StationarityStationarity is a common assumption in spatial statistics. The justification is often that stationarity is a reasonable approximation to…
Date:21 March 2018, Wednesday
Location:S16-06-118, DSAP Seminar Room
Time:03:00pm - 04:00pm
Distributed Kriging for Massive Spatial DataFlexible hierarchical Bayesian modeling of massive data is challenging due to poorly scaling computations in large sample size. This…
Date:28 February 2018, Wednesday
Location:S16-06-118, DSAP Seminar Room
Time:03:00pm - 04:00pm
Measures of University Research Output and Resource Usage EfficiencyThe management of universities demands data on teaching and research. While teaching parameters can be measured via student performance…