The Departments of Statistics and Computer Science at Purdue University
with additional support from Discovery park at Purdue University will
host a Machine Learning Summer School (MLSS, http://mlss.cc) from June
13 (Monday) to June 24 (Friday), 2011. This school is suitable for all
levels, both for people without previous knowledge in Machine Learning,
and those wishing to broaden their expertise in this area. Individuals
without previous knowledge will be able to learn more about the theory
and practice of Machine Learning, while those wishing to broaden their
expertise in this area will find the advanced courses particularly
useful. A partial list of confirmed speakers include:
* Leon Bottou, Microsoft Research
* Talk Title: Large-Scale Machine Learning and Stochastic Algorithms
* William Cleveland, Purdue University
* Talk Title: Divide and Recombine for the Analysis of Large Complex
Data sets
* Marina Meila, University of Washington
* Talk Title: Classic and modern data clustering
* Dale Schuurmans, University of Alberta, Canada
* Talk Title: Unified perspectives on supervised, unsupervised and
semi-supervised learning
* Satinder Singh (Baveja), University of Michigan, Ann Arbor.
* Talk Title: Reinforcement Learning: From Control to Artificial
Intelligence
* Alex Smola, Yahoo! research and Australian National University
* Talk Title: Graphical Models for the Internet
* Ben Taskar, University of Pennsylvania
* Talk Title: Structured Prediction
* Manfred Warmuth, University of California, Santa Cruz
* Talk Title: Recent advances in boosting and online learning
Thanks to generous sponsorship from NSF (support pending), AFOSR
(support pending), Computational Design and Innovation Lab, Microsoft
Research, IBM Research, and Pascal 2 a limited number of student
scholarships based on academic merit and need are available (see
website for priority ordering).
The total number of participants will be limited. So please register
early. For information visit our website
http://learning.stat.purdue.edu/wiki/mlss/start
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