Future directions in high-dimensional data analysis:

Workshop theme

This closing workshop of the research programme will look both backwards and forwards, although mainly the latter. There will be a retrospective component that reviews some of the ideas and advances that have been generated or initiated during the preceding six months, but the emphasis will be on presentations that look to the future, in this vital area of the analysis of large-scale data-sets. The invited speakers will include leading researchers from statistics and machine learning, and will describe theoretical/methodological advances as well as issues associated with implementation in important applied fields, such as finance, climatology, analysis of sparse signals and genomics.

Timetable

Monday 23rd June 2008
08:30 to 09:55	Registration	No Room Required
08:30 to 17:00	Poster session	Discussion Room
09:55 to 10:00	David Wallace - Welcome	No Room Required
10:00 to 11:00	Peter Hall University of Melbourne Variable selection in very high dimensional regression and classification	Room 1
11:00 to 11:30	Coffee	No Room Required
11:30 to 12:30	Ursula Gather Technische Universität Dortmund Dimension reduction	Room 1
12:30 to 13:30	Lunch at Wolfson Court	No Room Required
14:00 to 15:00	Nicolai Meinshausen University of California, Berkeley Stability - based regularisation	Room 1
15:00 to 15:30	Tea	No Room Required
15:30 to 16:30	Yuzhi Cai University of Plymouth Large-scale multiple testing: finding needles in a haystack	Room 1
16:30 to 17:30	Gong Show	No Room Required
17:30 to 18:30	Welcome Wine Reception and Poster Session	No Room Required
18:45 to 19:30	Dinner at Wolfson Court (Residents only)	No Room Required

Tuesday 24th June 2008
09:00 to 10:00	Hans van Houwelingen Universiteit Leiden Fitting survival models with P>>n predictors: beyond proportional hazards	Room 1
09:00 to 17:30	Poster session	Discussion Room
10:00 to 11:00	Ming Yuan Georgia Institute of Technology Model selection and estimation with multiple reproducing Karnel Hilbert spaces	Room 1
11:00 to 11:30	Coffee	No Room Required
11:30 to 12:30	Sparsity oracle inequalities	Room 1
12:30 to 13:30	Lunch at Wolfson Court	No Room Required
14:00 to 14:20	Edoardo Airoldi Princeton University The exchangeable graph model for statistical network analysis	Room 1
14:20 to 14:40	Mike West Duke University Data, models, inference and computation for dynamic cellular networks in systems biology	Room 1
14:40 to 15:00	Eric Xing Carnegie Mellon University Statistical network analysis and inference: methods and applications	Room 1
15:00 to 15:30	Tea	No Room Required
15:30 to 16:30	Ernst Wit Lancaster University High dimensional inference in bioinformatics and genomics	Room 1
16:30 to 17:30	Lexin Li North Carolina State University Liquid association for large scale gene expression and network studies	Room 1
18:45 to 19:30	Dinner at Wolfson Court (Residents only)	No Room Required

Wednesday 25th June 2008
09:00 to 10:00	Rob Tibshirani Stanford University The Lasso: some novel algorithms and applications	Room 1
10:00 to 11:00	John Shawe-Taylor University College London Sparsity in machine Learning: approaches and analyses	Room 1
11:00 to 11:30	Coffee	No Room Required
11:30 to 12:30	Art Owen Stanford University Transposably invariant sample reuse: the pigeonhole bootstrap and blockwise cross-validation	Room 1
12:30 to 13:30	Lunch at Wolfson Court	No Room Required
18:45 to 19:30	Dinner at Wolfson Court (Residents only)	No Room Required

Thursday 26th June 2008
09:00 to 10:00	Jane-Ling Wang University of California Covariate adjusted functional principal component analysis for longitudinal data	Room 1
10:00 to 11:00	Vladimir Koltchinskii Georgia Institute of Technology Penalized empirical risk minimization and sparse recovery problems	Room 1
11:00 to 11:30	Coffee	No Room Required
11:30 to 12:30	The Nystrom extension and spectral methods in learning: low-rank approximation of quadratic forms and products	Room 1
12:30 to 13:30	Lunch at Wolfson Court	No Room Required
14:00 to 14:20	Jianxin Pan University of Manchester Limiting theorems for large dimensional sample means, sample covariance matrices and Hotelling's T2 statistics	Room 1
14:20 to 14:40	Jian Qing Shi Newcastle University Generalised gaussian process functional regression model	Room 1
14:40 to 15:00	Jane-Ling Wang University of California Estimation of large volatility matrix for high-frequency financial data	Room 1
15:00 to 15:30	Tea	No Room Required
15:30 to 16:30	David Barber University College London Graph decomposition for community identification and covariance constraints	Room 1
16:30 to 17:30	Elizaveta Levina University of Michigan Permutation-invariant covariance regularisation in high dimensions	Room 1
19:30 to 23:00	Conference Dinner - Lucy Cavendish College (Hall)	No Room Required

Friday 27th June 2008
09:00 to 09:20	Inge Helland Universitetet i Oslo Optimal prediction from relevant components	Room 1
09:00 to 15:30	Poster session	Discussion Room
09:20 to 09:40	Inge Koch University of New South Wales Dimension selection with independent component analysis and its application to prediction	Room 1
09:40 to 10:00	Lexin Li North Carolina State University Model free variable selection via sufficient dimension reduction	Room 1
10:00 to 11:00	James Robins Harvard University Estimation of nonlinear functionals: recent results and open problems	Room 1
11:00 to 11:30	Coffee	No Room Required
11:30 to 12:30	Matthias Seeger Max-Planck-Institut für Biological Cybernetics, Tübingen Applications of approximate inference and experimental design for sparse (generalised) linear models	Room 1
12:30 to 13:30	Lunch at Wolfson Court	No Room Required
14:00 to 15:00	John Rice University of California, Berkeley Statistics in astronomy: the Taiwanese-American occultation survey	Room 1
15:00 to 15:30	Tea	No Room Required
18:45 to 19:30	Dinner at Wolfson Court (Residents only)	No Room Required

Future directions in high-dimensional data analysis:

Speakers

Edoardo Airoldi Princeton University
David Barber University College London
Yuzhi Cai University of Plymouth
Ursula Gather Technische Universität Dortmund
Peter Hall University of Melbourne
Inge Helland Universitetet i Oslo
Inge Koch University of New South Wales
Vladimir Koltchinskii Georgia Institute of Technology
Elizaveta Levina University of Michigan
Lexin Li North Carolina State University
Nicolai Meinshausen University of California, Berkeley
Art Owen Stanford University
Jianxin Pan University of Manchester
John Rice University of California, Berkeley
James Robins Harvard University
Matthias Seeger Max-Planck-Institut für Biological Cybernetics, Tübingen
John Shawe-Taylor University College London
Jian Qing Shi Newcastle University
Rob Tibshirani Stanford University
Hans van Houwelingen Universiteit Leiden
Jane-Ling Wang University of California
Mike West Duke University
Ernst Wit Lancaster University
Eric Xing Carnegie Mellon University
Ming Yuan Georgia Institute of Technology

Show All

Future directions in high-dimensional data analysis:

Workshop theme

Timetable

Speakers

Supported By

Register for updates