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SuSTaIn Events Sparsity workshop Invited speakers Programme Abstracts (pdf) Presentations, by author Group photo (jpg) Photo album Information for presenters Directions Joining instructions (pdf) Accommodation Conference dinner Restaurants Participation Flyer (pdf)
Sparse structures: statistical theory and practice
Research workshop, 16-18 June 2010



Invited Talks

Christophe Ambroise (CNRS) Inferring sparse gaussian graphical models for biological networks
Francois Caron (Bordeaux) Hierarchical models for dependent sparse linear regressions
Sara van de Geer (Zurich) The Lasso with within group structure
Chris Holmes (Oxford) Bayesian nonparametric clustering of sparse signals
Ann Lee (Carnegie Mellon) Exploiting sparse structure by spectral connectivity analysis
David Madigan (Columbia) Bayesian methods for drug safety surveillance
Alexandre Tsybakov (Paris VI) Estimation of high-dimensional low rank matrices
Martin Wainwright (Berkeley) Graphical model selection in high dimensions: Practical and information-theoretic limits
Marten Wegkamp (Florida State) Adaptive rank penalized estimators in multivariate regression

Contributed Talks

Nicolas Brunel (Evry) Sparse autoregressive models for module extraction in biological networks
Colin Campbell (Bristol) Multiple kernel learning methods for handling large and complex datasets
Haeran Cho (LSE) High-dimensional variable selection via tilting
Barbara Engelhardt (Chicago) Sparse factor analysis applied to biological problems
Florian Frommlet (Vienna) Asymptotic Bayes optimality under sparsity of multiple testing and model selection procedures
Paul Kirk (Imperial) Stability selection methods for biomarker discovery
Keith Knight (Toronto) Adaptive lasso for correlated predictors
Silvia Liverani(Bristol) Bayesian model selection on high-dimensional time series
Guillaume Obozinski (INRIA) Structured sparse principal component analysis
Jianxin Pan (Manchester) Modelling of large covariance matrices
Kevin Sharp (Manchester) Dense message passing for sparse principal component analysis
Andrew Smith (Bristol) Penalised regression on a graph
Sarel Steel (Stellenbosch) Variable selection for kernel classification


Vanna Albieri (Danish Cancer Society) A comparison of structural learning procedures for biological networks
Luke Bornn (British Columbia) The product graphical model
Colin Campbell (Bristol) Sparse regularisation methods for metric learning
Sohail Chand (Nottingham) Oracle properties of lasso-type methods
Tom Diethe (University College London) Learning in a Nystrom approximated space
Zhou Fang (Oxford) Group sparsity through concave penalties
Marie Fitch (Massey University, NZ) Sparsity vs computational convenience for estimation of a sparse inverse covariance matrix
Doyo Gragn (Open University) Sparse principal components based on semi-divisive clustering of genes
Shota Gugushvili (Vrije Universiteit Amsterdam) √n-consistent estimation for systems of ordinary differential equations: bypassing numerical integration via smoothing
Edmund Jones (Bristol) Graph distributions for Bayesian learning of sparse graphical model structures
Shakir Mohamed (Cambridge) Bayesian learning with correlated spike-and-slab priors
Dino Sejdinovic (Bristol) Message-passing algorithms in coding and information theory