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ISBA
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Tutorials - June 3
Contributed talks - in the late afternoons
Poster sessions - in the evenings June 3 through 7
Contributed
Talks
Thursday,
June 3, 2010
Session 1
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Stochastic models and
stochastic Monte Carlo
- Paul Blackwell (University of Sheffield)
- Layer counting for dating ice cores: A Bayesian
model-based approach
- Joaquin Miguez (Universidad Carlos III)
- Solving a class of global optimization problems by
way of Bayesian estimation methods
- Flavio Goncalves (University of Warwick)
- Exact Simulation and Bayesian Inference for
Jump-Diffusion Processes
- Natesh Pillai (University of Warwick)
- MCMC in high dimensions: A New Perspective
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Break
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Session 2
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Biostatistics
- Marina Savelieva (Novartis)
- Bayesian approach to Population PKPD Modelling:
advantages and drawbacks
- Milovan Krnjajic (National University of Ireland)
- Bayesian dynamic models for electronic medical
record data
- Sara Geneletti (London School of Economics)
- Uncovering selection bias in casecontrol studies
using Bayesian poststratificatio
- David Draper (University of California, Santa Cruz)
- A Bayesian Decision-Theoretic Alternative to
Standard Multiple-Comparisons Adjustments in Clinical Trials
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Friday,
June 4, 2010
Session 1
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Bioinformatics
- Paola Rancoita (Istituto Dalle Molle di Studi
sull'Intelligenza Artificiale)
- Bayesian Integrated Genomics
- Shane Jensen (The Wharton School)
- Bayesian Modeling of the Evolutionary Escape Response of HIV
- Christopher Yau (University of Oxford)
- Decision theoretic Bayesian nonparametric inference for the
molecular characterisation and stratification of colorectal cancer
using genome-wide microarrays
- Alan Lenarcic (Harvard University)
- A Bayesian Application of Lasso in Covariance Network Selection
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Break
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Session 2
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Jose Bernardo Honorary
session (decision theory and prior specification)
- Shakir Mohamed (University of Cambridge)
- Sparse Exponential Family Latent Variable Models
- Chris Hans (The Ohio State University)
- Penalized Regression via Orthant Normal
Priors
- Richard Hahn (Duke University)
- Sparse Partial Factor Regression
- Simon Lacoste-Julien (University of Cambridge)
- Approximate inference for the loss-calibrated
Bayesian
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Saturday,
June 5, 2010
Session 1
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Regression Models
- Sujit Ghosh (North Carolina State University)
- Bayesian Shape Restricted Regression with
Multivariate Bernstein Polynomials
- Alicia Quiros (Rey Juan Carlos University)
- Assessing the fit of regression models for multiple
imputation
- Anirban Bhattacharya (Duke University)
- Sparse Bayesian infinite factor models
- William Astle (Imperial College)
- A Bayesian model of NMR spectra for the
deconvolution and quantification of metabolites in complex biological
mixtures
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Break
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Session 2
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Statistical Computing
- Chris Holmes (University of Oxford)
- Bayesian Computation on Graphics Cards
- Andrew Parnell (University College Dublin)
- Fast joint posterior modelling through marginal
posterior mixtures
- Fabian Wauthier (University of California, Berkeley)
- Sparse Process Classification via the Gaussian
copula
- Jing Wang (University of Michigan)
- Approximate MCMC Simulation from Doubly-intractable
Distributions
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Monday,
June 7, 2010
Session 1
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Spatial and Temporal
Modeling
- Debdeep Pati (Duke University)
- Bayesian geostatistical modeling with informative
sampling locations
- Chris Paciorek (University of California, Berkeley)
- Flexible spatial latent variable modeling for
combining information
sources while accounting for systematic errors in proxies
- Carlos Almeida (Technische Universitaet Muenchen)
- Bayesian inference for time-varying pair-copula
constructions
- Ioanna Manolopoulou (Duke University)
- Inferences on dynamic point processes using mixture
models of spatio-temporal intensity functions
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Break
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Session 2
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Nonparametrics
- Yee Whye Teh (University College London)
- Hierarchical Bayesian Nonparametric Models for
Language and Text
- Subharup Guha (University of Missouri)
- Posterior Simulation in Countable Mixture
Models for Large Datasets
- Michalis Kolossiatis (Cyprus University of Technology)
- Modelling Via Normalisation for Bayesian
Nonparametric Inference
- Ferenc Huszar (University of Cambridge)
- Bayesian kernel machines: the third way of going
nonparametric
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Tuesday,
June 8, 2010
Session 1
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Graphical and network
models
- Edo Airoldi (Harvard University)
- Representation and Bayesian analysis of valued
networks
- Geoff Nicholls (Oxford University)
- Bayesian inference for a partial order from random
linear extensions
- Ricardo Henao (Technical University of Denmark and
University of Copenhagen)
- Learning Structure in Directed Acyclic Graphs with
Latent Variables
- Tyler McCormick (Columbia University)
- Latent Structure Models for Social Networks using Aggregated Relational Data
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Break
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Session 2
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Savage award finalists
- Emily Fox (Duke University)
- Bayesian Nonparametric Time Series Models for
Complex Dynamical Phenomena
- Matt Taddy (Chicago Booth)
- Dynamic Point Process Modeling with a DDP
- Ryan Adams (University of Toronto)
- Generative Modeling of Probability Densities with
Gaussian Processes
- James Scott (University of Texas at Austin)
- Robust Bayesian shrinkage in sparse
signal-extraction problems
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