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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).
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 |