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Seminars (SCHW01)

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Event When Speaker Title Presentation Material
SCHW01 7th January 2008
10:00 to 11:00
D Donoho Breakdown point of model selection when the number of variables exceeds the number of observations
SCHW01 7th January 2008
11:30 to 12:30
S van de Geer The deterministic lasso
SCHW01 7th January 2008
14:00 to 15:00
E Wegman Methods for visualizing high dimensional data
SCHW01 7th January 2008
15:30 to 16:30
A Young Bootstrap and parametric inference: successes and challenges
SCHW01 8th January 2008
09:00 to 10:00
M Wainwright Practical and information-theoretic limitations in high-dimensional inference
SCHW01 8th January 2008
10:00 to 11:00
R Samworth Some thoughts on nonparametric classification: nearest neighbours, bagging and max likelihood estimation of shape-constrained densities
SCHW01 8th January 2008
11:30 to 12:30
RD Cook Model-based sufficient dimension reduction for regression
SCHW01 8th January 2008
14:00 to 15:00
M Jordan Kernel-based contrast functions for sufficient dimension reduction
SCHW01 8th January 2008
15:30 to 16:30
J Fan Challenge of dimensionality in model selection and classification
SCHW01 8th January 2008
16:30 to 17:30
P Bickel Regularised estimation of high dimensional covariance matrices
SCHW01 9th January 2008
09:00 to 10:00
F Murtagh The ultrametric topology perspective on analysis of massive, very high dimensional data stores
SCHW01 9th January 2008
10:00 to 11:00
L Duembgen P-values for computer-intensive classifiers
SCHW01 9th January 2008
11:30 to 12:30
W Stuetzle Nonparametric cluster analysis: estimating the cluster tree of a density
SCHW01 9th January 2008
14:00 to 15:00
M West Sparsity modelling in large-scale dynamic models for portfolio analysis
SCHW01 9th January 2008
15:30 to 16:30
E Candes Computationally tractable statistical estimation when there are more variables than observations
SCHW01 9th January 2008
16:30 to 17:30
B Nadler Learning in high dimensions, noise, sparsity and treelets
SCHW01 10th January 2008
09:00 to 10:00
AW van der Vaart Estimating a response parameter in missing data models with high-dimensional covariates
SCHW01 10th January 2008
10:00 to 11:00
J Wellner Persistence: alternative proofs of some results of Greenshtein and Ritov
SCHW01 10th January 2008
11:30 to 12:30
D Cook Looking at models in high-dimensional data spaces
SCHW01 10th January 2008
14:00 to 15:00
J Tanner The surprising structure of Gaussian point clouds and its implications for signal processing
SCHW01 10th January 2008
15:30 to 16:30
A Lee Finding low-dimensional structure in high-dimensional data
SCHW01 10th January 2008
16:30 to 17:30
P Niyogi A geometric perspective on learning theory and algorithms
SCHW01 11th January 2008
09:00 to 10:00
P Buehlmann High-dimensional variable selection and graphs: sparsity, faithfulness and stability
SCHW01 11th January 2008
10:00 to 11:00
E Mammen Time series regression with semiparametric factor dynamics
SCHW01 11th January 2008
11:30 to 12:30
B Y Yu Using side information for prediction
SCHW01 11th January 2008
14:00 to 15:00
D Hoyle A physicist's approach to high-dimensional inference
SCHW01 11th January 2008
15:30 to 16:30
B Clarke Models, model lists, model spaces and predictive optimality
University of Cambridge Research Councils UK
    Clay Mathematics Institute London Mathematical Society NM Rothschild and Sons