========================================================== Call for Participation: MLSS Sydney 2015: Machine Learning Summer School 2015, Sydney, Australia February 16th to February 25th, 2015 http://www.nicta.com.au/mlss2015 Important dates (AEDT): Scholarship application deadline: December 15th, 2014 Early bird registration deadline: January 15th, 2015 Late registration: January 16th, 2015 to January 31st, 2015 ========================================================== Description ------------------------------------------------------------------------------- Machine Learning is a foundational discipline that forms the basis of much modern statistical data analysis. As data science emerges to meet the challenges of "Big Data", understanding the theory and practice of machine learning becomes a crucial asset in academia and industry. The machine learning summer school provides graduate students, academics and industry professionals with an intense learning experience on the theory and applications of modern machine learning. Over the course of eight days, a panel of internationally renowned experts in the field will offer tutorials covering basic as well as advanced topics. In addition, MLSS Sydney 2015 will feature hands-on sessions aimed at reinforcing the learned concepts through practice. Themes ------------------------------------------------------------------------------- The school will have a strong focus on probabilistic inference, large scale learning, Bayesian non-parametrics and applications to recommender systems, vision and document analysis. Confirmed Speakers and Topics ------------------------------------------------------------------------------- Ryan Adams (Harvard University) Bayesian Nonparametrics: Dirichlet Processes and Friends Wray Buntine (Monash University) Bayesian Non-parametric Methods for Unsupervised Models Bob Carpenter (Columbia University) Bayesian inference, MCMC and Stan Hands-on Justin Domke (NICTA) Probabilistic Graphical Models Stephen Gould (Australian National University) Structured Prediction for Computer Vision Alex Ihler (UCI Irvine) Approximate Inference Mark Johnson (Macquarie University) Natural Language Processing Alexandros Karatzoglou (Telefonica) ML for Recommender Systems Neil Lawrence (The University of Sheffield) Bayesian Nonparametrics: Gaussian Processes Frank Nielsen (Ecole Polytechnique) Computational Information Geometry and Machine Learning Richard Nock (NICTA) Boosting Lizhen Qu (NICTA ) Deep Learning Mark Reid (ANU and NICTA) Prediction Markets Mark Schmidt (University of British Columbia) Optimization Chris Webers (NICTA) Introduction to Machine Learning Organizers ------------------------------------------------------------------------------- Edwin V. Bonilla, The University of New South Wales Fabio Ramos, The University of Sydney Yang Wang, NICTA