Statistical Machine Learning reading group

The Statistical Machine Learning reading group is an informal forum for weekly talks and discussions about all areas of statistical machine learning and computational statistics. If you'd like to suggest a speaker, or to give a talk, or to present a paper, or brainstorm a half-baked idea, please let us know. Send mail to either Clay Scott (clayscot@umich), Long Nguyen (xuanlong@umich), Ambuj Tewari (tewaria@umich), or Laura Balzano (girasole@umich.edu).

Current Schedule

Fall 2013 Schedule

Wednesdays 11-12:30 at EECS 2311. Refer to Ctools site for presentation topics.

2012-2013 Schedule

Please check this link for the current schedule of the machine learning reading group.

Winter 2011 Schedule

When is it?Tuesday 11:30AM-12:30PM
Where is it?438 West Hall
March 8 Qiaozhu Mei
UM School of Information and EECS
Talk title: Topic modeling with network regularization
March 15 Yves Atchade
UM Statistics
Talk title: Estimation of network structures by \ell_1 penalized pseudo-likelihood: some asymptotic results.
March 22 John Lafferty,
CMU Computer Science, Machine Learning and Statistics
Department Seminar Series (Joint with AI Seminar in EECS)
Talk cancelled
4:00 pm 340 WH
March 29 Chris Miller
UM Astronomy
Accurate parameter estimation for star formation history in galaxies using SDSS spectra
April 5 George Michailidis
UM Statistics
Talk title: Estimating Network Granger Causality
April 12 Honglak Lee
UM EECS
Talk title: Unsupervised generative learning of sparse, distributed, convolutional feature representations
April 19 Al Hero
UM EECS and Statistics
Talk title: Correlation screening in high dimension
April 26 Edward Ionides
UM Statistics
Talk title: Feature matching versus likelihood for dynamic systems: Nicholson's blowflies as a case study