Apr
7
2:00 pm14:00

### Week 33 ###

Presenter: Bin Peng
Paper: Another Look on a Semiparametric Single-Index Model
Author(s): Chaohua Dong, Jiti Gao and Bin Peng
Link: [not yet public - will be distributed via email]

Mar
24
3:00 pm15:00

### Week 31b ###

Presenter: Heike Hofmann (Iowa State)
Title: Visual Inference - Examples and Discussion
Abstract: How do you know if something you see in a data plot is really there? Visual inference allows us to find an answer to these questions similar to classical statistical hypothesis testing. Visual inference is based on non-parametric inferential methods using human observers to establish the relevance of graphical findings, thereby creating a bridge between classical statistical inference and exploratory data analysis. Based on the seminal paper by Buja et al (2009), I will start with the lineup protocol, give examples where visual inference has allowed us to gain insight beyond classical modeling situations, and go into a discussion of some of the still open questions on visual inference.
Location: CB04.05.430 (Grid Room)

Mar
11
11:00 am11:00

### Week 29 ###

Presenter: Scott Sisson (UNSW)
Main Paper: Diagnostic Tools for Approximate Bayesian Computation Using the Coverage Property
Author(s): Prangle, D., Blum, M.G.B., Popovic, G., Sisson, S.A.
Link: http://onlinelibrary.wiley.com/doi/10.1111/anzs.12087/abstract [journal] http://arxiv.org/pdf/1301.3166.pdf [open source preprint]

Background Paper: Validation of Software for Bayesian Models Using Posterior Quantiles
Author(s): Cook, S.R., Gelman, A., Rubin, D.B.
Link: http://www.stat.columbia.edu/~gelman/research/published/Cook_Software_Validation.pdf

Dec
10
3:00 pm15:00

### Week 23 ###

Presenter: Hon Hwang et al.
Topic: An informal overview and showcase of deep learning methodologies in machine learning and statistics.

Nov
20
3:00 pm15:00

### Week 20 ###

Presenter: Simon Byrne (University College London)
Paper: Geodesic Monte Carlo (with discussion)
Author(s): Simon Byrne, Mark Girolami
Link: http://arxiv.org/abs/1301.6064 [paper] http://onlinelibrary.wiley.com/doi/10.1111/sjos.v41.1/issuetoc [discussion]

Oct
22
3:00 pm15:00

### Week 17 ###

Presenter: Deborah Street
Paper: Latin Hypercubes and Space-filling design; in Handbook of Design and Analysis of Experiment, eds. Angela Dean, Max Morris, John Stufken, Derek Bingham
Author(s): C. Devon Lin and Boxin Tan
Link: NA

 

Oct
14
3:00 pm15:00

### Week 16 ###

Presenter: Stephen Wright
Paper: Nonparametric bayes modeling for case control studies with many predictors
Author(s): Jing Zhou, Amy H. Herring, Anirban Bhattacharya, Andrew F. Olshan, David B. Dunson and The National Birth Defects Prevention Study
Link: http://dx.doi.org/10.1111/biom.12411

 

Oct
1
3:00 pm15:00

### Week 14 ###

Presenter: Louise Ryan
Paper: Identification of important regressor groups, subgroups and individuals via regularization methods: application to gut microbiome data
Author(s): Tanya Garcia, Samuel Muller, Raymond Carroll, Rosemary Walzem
Link: http://bioinformatics.oxfordjournals.org/content/30/6/831.full.pdf

 

Sep
24
3:00 pm15:00

### Week 13 ###

Presenter: Chris Oates
Paper: Frequentist Coverage of Adaptive Nonparametric Bayesian Credible Sets (with discussion)
Author(s): Botond Szabó, Aad van der Vaart, Harry van Zanten
Link: http://arxiv.org/pdf/1310.4489v5.pdf [paper] https://projecteuclid.org/euclid.aos/1434546202 [discussion]

 

Sep
17
3:00 pm15:00

### Week 12 ###

Presenter: Craig Anderson
Paper: A multi-resolution approximation for massive spatial datasets
Author(s): Matthias Katzfuss
Link: http://arxiv.org/pdf/1507.04789v1.pdf

 

Sep
10
3:00 pm15:00

### Week 11 ###

Presenter: Cathy Lee
Paper: Inferring Causal Impact Using Bayesian Structural Time-Series Models
Author(s): Kay H. Brodersen, Fabian Gallusser, Jim Koehler, Nicolas Remy, Steven L. Scott
Link: http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/41854.pdf

 

Sep
3
3:00 pm15:00

### Week 10 ###

Presenter: Stephen Wright
Paper(s): A Statistical Perspective on Algorithmic Leveraging // Leveraging for Big Data Regression
Author(s): Ping Ma, Michael W. Mahoney, Bin Yu, Xiaoxiao Sun
Link(s): http://jmlr.org/proceedings/papers/v32/ma14.pdf and http://onlinelibrary.wiley.com/doi/10.1002/wics.1324/pdf

 

Aug
27
3:00 pm15:00

### Week 9 ###

Presenter: Chris Evenhuis
Paper: Sequential Kernel Herding: Frank-Wolfe Optimization for Particle Filtering
Author(s): Simon Lacoste-Julien, Fredrik Lindsten, Francis Bach
Link: http://arxiv.org/pdf/1501.02056v2.pdf