Machine Learning Group

Welcome to the Machine Learning Group (MLG). We are a small group of researchers with shared interests in machine learning. We work on a variety of topics spanning theoretical foundations, algorithms, and applications.


NEWS

July 10-15 Suvrit Sra lecturing at the PKU Applied Math Summer School (Beijing, China), on Optimization for Machine Learning: Convex and Nonconvex
Aug 24 Stefanie Jegelka holding a bootcamp lecture at the Simons Institute, Berkeley on Continuous methods for Discrete Optimization
Jun 27 Stefanie Jegelka lecturing at the Machine Learning Summer School (MLSS), Tübingen, Germany, on Submodularity in ML
Jun 26,27 Suvrit Sra lecturing at the Machine Learning Summer School (MLSS), Tübingen, Germany, on Optimization for ML
13 May 9 ICML 2017 Papers by MLG. Congrats!
06 Apr Boston Globe features 6.036: Introduction to Machine Learning
(featuring Tommi Jaakkola and Regina Barzilay)
20 Jun   T. Broderick co-organizing Statistical Inference for Network Models Symposium at NetSci 2017
Feb '17   Prof. Tamara Broderick receives a Google Faculty Research award. Congrats!
Jan '17   Prof. Tamara Broderick holding a Simons Institute Tutorial on Nonparameteric Bayesian Methods in ML.
Jan '17   Prof. Stefanie Jegelka holding a Simons Institute Tutorial on Submodularity in Machine Learning: Theory and Applications.
Fall '16   Welcome new ML graduate students!
Dec '16   Suvrit Sra holding a NIPS Tutorial (with F. Bach)
Dec '16 MLG members organizing 4 NIPS workshops: [1]; [2]; [3]; [4]
Aug '16   18 papers accepted to NIPS 2016. Congrats!
May '16   8 papers accepted to ICML 2016. Congrats!

Fun on Visit Day!