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Statistics Reading Group
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Description to be confirmed If you have a question about this list, please contact: HoD Secretary, DPMMS; Richard Samworth; Richard Nickl; D. Finucane; mh332. If you have a question about a specific talk, click on that talk to find its organiser. 0 upcoming talks and 46 talks in the archive. Reproducing Kernel Hilbert Spaces in Non-parametric StatisticsNote the unusual time and location to allow attendance at the RSS Ordinary meeting
Minimax lower bound using Assouad's method
Adaptive algorithms for Stratified Sampling Monte CarloNote the earlier time and different room to allow attendance at the RSS Ordinary Meeting
Theory and applications of proper scoring rules
Graphical communication of variability, risk and uncertainty
Modern advances in likelihood ratio inference
Robust Statistics: An Overview and Some Questions
Statistical problems in Astronomy and High Energy Physics
Statistical image processing for electron microscopy on molecular machines
Bayesian Clustering with the Dirichlet-Process Prior
Nonparametric maximum likelihood estimation
Compressed sensing: Lecture 8
Generalized sampling and infinite-dimensional compressed sensing
Compressed sensing: Lecture 7
Compressed sensing: Lecture 6
Minimisation of sparse higher-order energies for large-scale problems in imaging
Compressed sensing: Lecture 5
Compressed sensing: Lecture 4
The Dantzig selector for high dimensional statistical problems
Compressed sensing: Lecture 3
Compressed sensing: Lecture 2
Compressed Sensing in RF
Compressed sensing: Lecture 1
Model criticism in complex Bayesian evidence synthesis for infectious disease models
Nonparametric maximum likelihood estimation
Frameworks for causal inference
Online Expectation-Maximisation
Recent Advances in Particle Based Simulation Methods
Variational methods continued
An Introduction to Variational Methods for Approximate Inference in Graphical Models
New approaches to Bayesian asymptotics
An introduction to sequential Monte Carlo methods
Compressed Sensing - Introduction and Future Aspects
Bayesian Nonparametric Mixture Models
When can we quantify uncertainty?
The EM algorithm and applications
Ferguson's 1973 paper on the Dirichlet process
Learning based on Data Compression
The 1995 Benjamini and Hochberg paper on false discovery rates
The 1995 wavelet paper of Donoho, Johnstone, Kerkyacharian and Picard
Ronald Fisher's 1934 likelihood and inference paper
David Cox's 1972 proportional hazards paper
Charles Stein's 1956 inadmissibility paper
Please see above for contact details for this list. |
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Bharath Sriperumbudur, Statistical Laboratory.
Wednesday 13 March 2013, 13:15-14:30