Statistical Inference for Large Scale Data
Speakers
Details
Very large data sets lead naturally to the development of very complex models --- often models with more adjustable parameters than data. This has led very recently to a rapidly growing body of work in the development and analysis of formal statistical tools for use in these big data problems – often in high dimensions. This workshop will explore, delineate, and make progress on open theoretical issues in the statistical aspects of Large Scale Inference.
Additional Information
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Registration for this event is now open. The registration fee is $100 for faculty members and $50 for graduate students or post-docs. Particpants will be required to register with PIMS and then return to the signup page and select the registration button for payment.
Program/Abstracts
An event program and abstracts for the speakers are available on the following website:
http://people.stat.sfu.ca/~lockhart/richard/SILSD/
- Jacob Bien, Cornell
- Andreas Buja, Wharton
- Venkat Chandrasekaran, Caltech
- Johannes Lederer, Cornell
- Jason Lee, Stanford
- Hannes Leeb, Vienna
- Po-Ling Loh, Wharton
- Aurelie Lozano, IBM Research
- Richard Samworth, Cambridge
- Noah Simon, Washington
- Jonathan Taylor, Stanford
- Rob Tibshirani, Stanford
- Bin Yu, Berkeley
- Ming Yuan, Wisconsin
- Tong Zhang, Rutgers
- Ji Zhu, Michigan
