WORKSHOP
STATISTICAL INFERENCE IN
COMPLEX/HIGH-DIMENSIONAL PROBLEMS

Invited Session 8, Lecture Hall C2
Chair: Keith Knight

Rudy Beran (UC Davis):
Hypercube Estimators: Penalized Least Squares, Submodel Selection and Numerical Stability (Abstract)   

Contributed Session 4a, Lecture Hall C2
Chair: Richard Nickl

Adam Bull (University of Cambridge):
Honest Adaptive Confidence Bands and Self-Similar Functions (Abstract)   

Bartek Knapik (Free University Amsterdam):
Adaptive Bayesian Procedures for Inverse Problems (Abstract)   

Hannes Leeb (University of Vienna):
On the Conditional Distributions of Low-Dimensional Projections from High-Dimensional Data (Abstract)   

Contributed Session 4b, Lecture Hall A
Chair: Ulrike Schneider

Andreas Artemiou (Michigan Technological University):
On the Use of Machine Learning Techniques in Sufficient Dimension Reduction (Abstract)   

Cheng Cheng (St. Jude Children's Research Hospital):
Context Directed Discovery of Stochastic Dependence in Ultrahigh Dimensional Genomics: An Alternative to Model Selection (Abstract)   

Zhu Wang (University of Connecticut School of Medicine):
HingeBoost: ROC-Based Boost for Classification and Variable Selection (Abstract)   

Invited Session 9, Lecture Hall C2
Chair: Manfred Deistler

Bruce E. Hansen (University of Wisconsin):
Efficient Shrinkage in Parametric Models (Abstract)   

Invited Session 10, Lecture Hall C2
Chair: Cun-Hui Zhang

Tianxi Cai (Harvard School of Public Health):
Omnibus Risk Assessment via Accelerated Failure Time Kernel Machine Modeling (Abstract)   

Invited Session 11, Lecture Hall C2
Chair: Rudy Beran

Emmanuel Candes (Stanford University):
The Limits of Adaptive Sensing (Abstract)   

Closing Session, Lecture Hall C2