CSML Master Classes
The CSML Master Class Series invites distinguished speakers from all over the world to spend several days at CSML to present their work in depth during seminars and meetings.
The CSML Master Class Series is sponsored by DeepMind Technologies (www.deepmind.com). DeepMind Technologies is an ambitious London-based startup building general-purpose learning algorithms, with initial product applications in mobile social gaming.iCalendar URL for all master classes: www.csml.ac.uk/ics/type/4
Upcoming Master Classes
Previous Master Classes
Martin Wainwright is currently a professor at University of California at Berkeley, with a joint appointment between the Department of Statistics and the Department of Electrical Engineering and Computer Sciences (EECS). He received a Bachelor's degree in Mathematics from University of Waterloo, Canada, and Ph.D. degree in EECS from Massachusetts Institute of Technology (MIT). His research interests include high-dimensional statistics, statistical machine learning, information theory and statistical signal processing. He is currently serving as an associate editor for the Annals of Statistics, Journal of Machine Learning Research, and Information and Inference.
He has been awarded the George M. Sprowls Prize for his dissertation research (MIT), an Alfred P. Sloan Foundation Fellowship, Best Paper Awards from the IEEE Signal Processing Society (2008), IEEE Communications Society (2010), the Joint Paper Prize (2012) from IEEE Information Theory and Communication Societies, and a Medallion Lecturer (2013) from the Institute of Mathematical Statistics.The slides for the talks are available here: Lecture 1, Lecture 2 (paper), Lecture 3 (paper)
Arnaud Doucet (Professor of Statistics, Department of Statistics, Oxford University) will be the second speaker in the CSML Master Class Series.
Arnaud Doucet obtained his PhD Degree from University Paris XI in 1997. He has held previously faculty positions at the University of Melbourne, the University of Cambridge, the Institute of Statistical Mathematics in Tokyo and was a Canada Research Chair at the University of British Columbia. He joined the Department of Statistics of the University of Oxford in 2011 where he is currently Professor. He is Associate editor of the Annals of Statistics and ACM Transactions on Modeling and Computer Simulation. His research areas include Monte Carlo methods, Bayesian statistics, dynamic models and their applicationsThe slides for the talks are available here: ucl_1.pdf, ucl_2.pdf, ucl_3.pdf
Larry Wasserman is Professor of Statistics at Carnegie Mellon University. He is also a member of the Center for Automated Learning and Discovery in the School of Computer Science. His research areas include nonparametric inference, asymptotic theory, causality, and applications to astrophysics, bioinformatics, and genetics. He is the 1999 winner of the Committee of Presidents of Statistical Societies Presidents' Award and the 2002 winner of the Centre de recherches mathematiques de Montreal Statistical Society of Canada Prize in Statistics. He is Associate Editor of The Journal of the American Statistical Association and The Annals of Statistics. He is a fellow of the American Statistical Association and of the Institute of Mathematical Statistics.