<div dir="ltr"><div><div class="gmail_signature"><div dir="ltr"><div><span style="font-size:12.6666669845581px">==========================================</span><span style="font-size:12.6666669845581px"><br></span></div><div><span style="font-size:12.6666669845581px"> APPLICATIONS NOW OPEN FOR</span></div><div><span style="font-size:12.6666669845581px">==========================================</span><br style="font-size:12.6666669845581px"><span style="font-size:12.6666669845581px"> the 29th MACHINE LEARNING SUMMER SCHOOL</span><br style="font-size:12.6666669845581px"><span style="font-size:12.6666669845581px"> in Kyoto University, Japan,</span></div><div><span style="font-size:12.6666669845581px"> 23 August to 4 September 2015.</span></div><div><span style="font-size:12.6666669845581px"> *** <a href="http://www.i.kyoto-u.ac.jp/mlss15">http://www.i.kyoto-u.ac.jp/mlss15</a> ***</span><br></div><div><span style="font-size:12.6666669845581px">==========================================</span><br style="font-size:12.6666669845581px"><br>Dear Colleagues,<br><div><br></div><div>Building upon the great success of the MLSS'12 in Kyoto </div><div>(~300 participants from 50 countries, ~20 lecturers, ~75 hours of lectures), </div><div>we are organizing another Machine Learning Summer School </div><div>this summer, to be held again in Kyoto University, Japan,</div><div>from August 23 to September 4.<br></div><div><br></div><div>This edition will be the 29th in the now longstanding MLSS series. (<a href="http://mlss.cc">http://mlss.cc</a>)</div><div><br></div><div>Please share with your colleagues and students this fantastic opportunity to:</div><div>- learn from world-renowned machine learning specialists,</div><div>- network with a diverse and formidable audience,</div><div>- discover and enjoy Kyoto, one of the most beautiful cities in the world! (<a href="http://kyoto.travel/en">http://kyoto.travel/en</a>)</div><div><br></div><div>We provide below an overview of the MLSS program and application process. More detailed information is available on our website: <span style="font-size:12.6666669845581px"><a href="http://www.i.kyoto-u.ac.jp/mlss15">http://www.i.kyoto-u.ac.jp/mlss15</a></span></div><div><br></div><div>We hope to see you in Kyoto this summer!</div><div>With regards</div><div><br></div><div>The organizers,</div><div><span style="font-size:12.6666669845581px">M. Cuturi </span><span style="font-size:12.6666669845581px">(Kyoto U.)</span><span style="font-size:12.6666669845581px">, A. Yamamoto (Kyoto U.), M. Sugiyama (U. of Tokyo)</span><br></div><div><br></div><span style="font-size:12.6666669845581px">============================================</span><br style="font-size:12.6666669845581px"><span style="font-size:12.6666669845581px">Scope</span><br style="font-size:12.6666669845581px"><span style="font-size:12.6666669845581px">============================================</span><br style="font-size:12.6666669845581px"><span style="font-size:12.6666669845581px"><br></span></div><div><span style="font-size:12.6666669845581px">The machine learning summer school provides advanced-undergraduate </span></div><div><span style="font-size:12.6666669845581px">and graduate students, industry professionals and academics of all levels</span><span style="font-size:12.6666669845581px"> </span></div><div><span style="font-size:12.6666669845581px">with an intense learning experience on the theory and </span><span style="font-size:12.6666669845581px">applications of modern </span></div><div><span style="font-size:12.6666669845581px">machine learning. </span></div><div><span style="font-size:12.6666669845581px"><br></span></div><div><span style="font-size:12.6666669845581px">Over the course of two weeks, </span><span style="font-size:12.6666669845581px">a panel of internationally </span><span style="font-size:12.6666669845581px">renowned lecturers </span></div><div><span style="font-size:12.6666669845581px">will offer </span><span style="font-size:12.6666669845581px">tutorials covering basic as </span><span style="font-size:12.6666669845581px">well as advanced topics. </span></div><div><span style="font-size:12.6666669845581px"><br></span></div><div><span style="font-size:12.6666669845581px">The summer school will allow the participants to get in touch with </span><span style="font-size:12.6666669845581px">international experts </span></div><div><span style="font-size:12.6666669845581px">in this field. </span><span style="font-size:12.6666669845581px">Joint publications, new research projects </span><span style="font-size:12.6666669845581px">and exciting opportunities will </span></div><div><span style="font-size:12.6666669845581px">arise from these interactions.</span></div><div><br style="font-size:12.6666669845581px"><span style="font-size:12.6666669845581px">============================================</span><br style="font-size:12.6666669845581px"><span style="font-size:12.6666669845581px">Confirmed Speakers and Topics</span><br style="font-size:12.6666669845581px"><span style="font-size:12.6666669845581px">============================================</span><br style="font-size:12.6666669845581px"><br style="font-size:12.6666669845581px"><div><span style="font-size:12.6666669845581px">Stephen P. Boyd, </span><span style="font-size:12.6666669845581px">Stanford </span></div><div><span style="font-size:12.6666669845581px"> </span><span style="font-size:12.6666669845581px"> </span><span style="font-size:12.6666669845581px">Convex Optimization</span></div><div><span style="font-size:12.6666669845581px"><br></span></div><div><span style="font-size:12.6666669845581px">Emmanuel Candès, </span><span style="font-size:12.6666669845581px">Stanford</span></div><div><span style="font-size:12.6666669845581px"> </span><span style="font-size:12.6666669845581px"> </span><span style="font-size:12.6666669845581px">Topics in High-Dimensional Statistics</span></div><div><span style="font-size:12.6666669845581px"><br></span></div><div><span style="font-size:12.6666669845581px">Zaid Harchaoui, </span><span style="font-size:12.6666669845581px">NYU/INRIA</span></div><div><span style="font-size:12.6666669845581px"> </span><span style="font-size:12.6666669845581px"> </span><span style="font-size:12.6666669845581px">Machine Learning for Computer Vision</span></div><div><span style="font-size:12.6666669845581px"><br></span></div><div><span style="font-size:12.6666669845581px">Stefanie Jegelka, </span><span style="font-size:12.6666669845581px">MIT</span></div><div><span style="font-size:12.6666669845581px"> </span><span style="font-size:12.6666669845581px"> </span><span style="font-size:12.6666669845581px">Submodular Functions in Machine Learning</span></div><div><span style="font-size:12.6666669845581px"><br></span></div><div><span style="font-size:12.6666669845581px">Gábor Lugosi, </span><span style="font-size:12.6666669845581px">Pompeu Fabra</span></div><div><span style="font-size:12.6666669845581px"> </span><span style="font-size:12.6666669845581px"> </span><span style="font-size:12.6666669845581px">Concentration Inequalities for Machine Learning</span></div><div><span style="font-size:12.6666669845581px"><br></span></div><div><span style="font-size:12.6666669845581px">Luc de Raedt, KU Leuven</span></div><div><span style="font-size:12.6666669845581px"> Probabilistic Programming</span></div><div><span style="font-size:12.6666669845581px"><br></span></div><div><span style="font-size:12.6666669845581px">Philippe Rigollet, </span><span style="font-size:12.6666669845581px">MIT</span></div><div><span style="font-size:12.6666669845581px"> </span><span style="font-size:12.6666669845581px"> </span><span style="font-size:12.6666669845581px">Statistical and Computational Aspects of High-Dimensional Learning</span></div><div><span style="font-size:12.6666669845581px"><br></span></div><div><span style="font-size:12.6666669845581px">Lorenzo Rosasco, </span><span style="font-size:12.6666669845581px">MIT / Genoa</span></div><div><span style="font-size:12.6666669845581px"> Learning Representations</span></div><div><span style="font-size:12.6666669845581px"><br></span></div><div><span style="font-size:12.6666669845581px">Alexander J. Smola, </span><span style="font-size:12.6666669845581px">CMU</span></div><div><span style="font-size:12.6666669845581px"> Scalable Machine Learning</span></div><div><br></div><div><span style="font-size:12.6666669845581px">Taiji Suzuki, </span><span style="font-size:12.6666669845581px">Tokyo Tech</span></div><div><span style="font-size:12.6666669845581px"> </span><span style="font-size:12.6666669845581px"> </span><span style="font-size:12.6666669845581px">Stochastic Optimization</span></div><div><span style="font-size:12.6666669845581px"><br></span></div><div><span style="font-size:12.6666669845581px">Csaba Szepesvári, U. of </span><span style="font-size:12.6666669845581px">Alberta</span></div><div><span style="font-size:12.6666669845581px"> </span><span style="font-size:12.6666669845581px"> </span><span style="font-size:12.6666669845581px">Reinforcement Learning</span></div><div><br></div><div><span style="font-size:12.6666669845581px">Ryota Tomioka, </span><span style="font-size:12.6666669845581px">TTI Chicago</span></div><div><span style="font-size:12.6666669845581px"> </span><span style="font-size:12.6666669845581px"> </span><span style="font-size:12.6666669845581px">Tensor Decompositions in Machine Learning</span></div><div><br></div><div><span style="font-size:12.6666669845581px">Vincent Vanhoucke, </span><span style="font-size:12.6666669845581px">Google</span></div><div><span style="font-size:12.6666669845581px"> </span><span style="font-size:12.6666669845581px"> </span><span style="font-size:12.6666669845581px">Large Scale Deep Learning</span></div><div><span style="font-size:12.6666669845581px"><br></span></div><div><span style="font-size:12.6666669845581px">Martin Wainwright, </span><span style="font-size:12.6666669845581px">Berkeley</span></div><div><span style="font-size:12.6666669845581px"> </span><span style="font-size:12.6666669845581px"> </span><span style="font-size:12.6666669845581px">Statistical Guarantees in Optimization</span></div><div><br></div><div><br></div><span style="font-size:12.6666669845581px"><div><span style="font-size:12.6666669845581px">============================================</span><span style="font-size:12.6666669845581px"><br></span></div>Who Can Apply?</span><br style="font-size:12.6666669845581px"><span style="font-size:12.6666669845581px">============================================</span><br style="font-size:12.6666669845581px"><div style><span style="font-size:12.6666669845581px">Anyone can apply from January 22 to April 10: the summer school is targeted for students (specially at a master/PhD level), academics (faculty, researchers and postdoctoral researchers) and professionals </span><span style="font-size:12.6666669845581px">looking to use, </span><span style="font-size:12.6666669845581px">or already using machine </span><span style="font-size:12.6666669845581px">learning methods in their work.</span></div><div style><span style="font-size:12.6666669845581px"><br></span></div><div style><span style="font-size:12.6666669845581px">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.</span></div><div style><span style="font-size:12.6666669845581px"><br></span></div><div style>Student applicants (and students only) can apply for financial support to cover their trip expenses. Financial support will be given in priority to students who would not be able to attend the summer school without financial help or a registration fee waiver, despite having an excellent academic background and a previously demonstrated interest in machine learning or any related discipline. The limited support funds we have will be allocated on a competitive basis, upon reviewing application documents.<br></div></div><div><br></div><div><span style="font-size:12.6666669845581px">============================================</span><br></div><div><span style="font-size:12.6666669845581px">Application Process</span><br style="font-size:12.6666669845581px"><span style="font-size:12.6666669845581px">============================================</span></div><div><span style="font-size:12.6666669845581px"><br></span></div><div><span style="font-size:12.6666669845581px">Applicants will be asked to submit a CV, a cover letter</span><span style="font-size:12.6666669845581px">, and, for student applicants only, </span></div><div><span style="font-size:12.6666669845581px">a short letter of recommendation </span><span style="font-size:12.6666669845581px">(to be submitted electronically) from one referee </span><span style="font-size:12.6666669845581px">of their </span><span style="font-size:12.6666669845581px">choice. </span></div><div><span style="font-size:12.6666669845581px"><br></span></div><div><span style="font-size:12.6666669845581px">Participants are encouraged to discuss their </span><span style="font-size:12.6666669845581px">own work with their peers and the speakers. </span></div><div><span style="font-size:12.6666669845581px">Applicants are thus invited </span><span style="font-size:12.6666669845581px">to provide the title/abstract of a poster they would like to </span></div><div><span style="font-size:12.6666669845581px">present at the school.</span></div><div><span style="font-size:12.6666669845581px"><br></span></div><div>Please apply here: <a href="http://www.iip.ist.i.kyoto-u.ac.jp/mlss15/doku.php?id=application">http://www.iip.ist.i.kyoto-u.ac.jp/mlss15/doku.php?id=application</a><span style="font-size:12.6666669845581px"><br></span></div><div><span style="font-size:12.6666669845581px"><br></span></div><div><span style="font-size:12.6666669845581px">============================================</span><span style="font-size:12.6666669845581px"><br></span></div><div><span style="font-size:12.6666669845581px">Important Dates</span><br style="font-size:12.6666669845581px"></div><div><span style="font-size:12.6666669845581px">============================================</span><span style="font-size:12.6666669845581px"><br></span></div><div><div style><span style="font-size:12.6666669845581px"><br></span></div><div style><span style="font-size:12.6666669845581px">Application Opens: January 22 (NOW!)</span></div><div style><span style="font-size:12.6666669845581px">Application Deadline: April 10. </span></div><div style><span style="font-size:12.6666669845581px">Acceptance notification: April 24.</span><br></div></div><div><span style="font-size:12.6666669845581px">Registration Fees Payment Deadline: May 12.</span></div><div><span style="font-size:12.6666669845581px">Summer School Dates: August 23 (Sun.) - September 4 (Fri.)</span></div><div><span style="font-size:12.6666669845581px"><br></span></div><div><span style="font-size:12.6666669845581px">============================================</span><span style="font-size:12.6666669845581px"><br></span></div><div><span style="font-size:12.6666669845581px">For inquiries, please contact:</span></div><div><span style="font-size:12.6666669845581px"><a href="mailto:mlss.kyoto.2015@gmail.com">mlss.kyoto.2015@gmail.com</a></span></div><div><span style="font-size:12.6666669845581px">============================================</span></div><div><span style="font-size:12.6666669845581px"><br></span></div></div></div></div>
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