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- | ===== 講義スケジュール ===== | + | ===== Schedule ===== |
- | **開催日時: 8/23 (日) から 9/4(金) まで** | + | **Dates: August 23rd (Sun) to September 4th (Fri), 2015. ** |
<html> | <html> | ||
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<td style="background-color: #FFDAB9"></html>[[schedule#Submodular Functions|Jegelka]]<html></td> | <td style="background-color: #FFDAB9"></html>[[schedule#Submodular Functions|Jegelka]]<html></td> | ||
<td style="background-color: #FAA992"></html>[[schedule#Statistical and Computational Aspects of High-Dimensional Learning|Rigollet]]<html></td> | <td style="background-color: #FAA992"></html>[[schedule#Statistical and Computational Aspects of High-Dimensional Learning|Rigollet]]<html></td> | ||
- | <td style="background-color: #cf0000; color: #fff;" >Kyoto U.</td> | + | <td style="background-color: #cf0000; color: #fff;" ></html>[[schedule#Kyoto U. Session|Kyoto U.]]<html></td> |
<td style="background-color: #DEAFAF"></html>[[schedule#Scalable Machine Learning|Smola]]<html></td> | <td style="background-color: #DEAFAF"></html>[[schedule#Scalable Machine Learning|Smola]]<html></td> | ||
</tr> | </tr> | ||
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</html> | </html> | ||
- | <html> | ||
- | <table class="uk-table uk-table-condensed"> | ||
- | <tr> | ||
- | <td style="width:100px;"></td> | ||
- | <td style="width:100px;">Sun. 23rd</td> | ||
- | <td style="width:100px;">Mon. 24th</td> | ||
- | <td style="width:100px;">Tue. 25th</td> | ||
- | <td style="width:100px;">Wed. 26th</td> | ||
- | <td style="width:100px;">Thu. 27th</td> | ||
- | <td style="width:100px;">Fri. 28th</td> | ||
- | </tr> | ||
- | <tr> | ||
- | <td>8:30-10:00</td> | ||
- | <td style="background-color: #ffff00"></html>[[schedule#Registration and Opening Statements|Registration]]<html></td> | ||
- | <td style="background-color: #8FBC8F"></html>[[schedule#Topics in Selective Inference|Candès]]<html></td> | ||
- | <td style="background-color: #8FBC8F"></html>[[schedule#Topics in Selective Inference|Candès]]<html></td> | ||
- | <td style="background-color: #FFDAB9"></html>[[schedule#Submodular Functions|Jegelka]]<html></td> | ||
- | <td style="background-color: #DEAFAF"></html>[[schedule#Scalable Machine Learning|Smola]]<html></td> | ||
- | <td></td> | ||
- | </tr> | ||
- | <tr> | ||
- | <td>10:30-12:00</td> | ||
- | <td style="background-color: #FAEBD7"></html>[[schedule#Convex Optimization|Boyd]]<html></td> | ||
- | <td style="background-color: #8FBC8F"></html>[[schedule#Topics in Selective Inference|Candès]]<html></td> | ||
- | <td style="background-color: #FFDAB9"></html>[[schedule#Submodular Functions|Jegelka]]<html></td> | ||
- | <td style="background-color: #FAA992"></html>[[schedule#Statistical and Computational Aspects of High-Dimensional Learning|Rigollet]]<html></td> | ||
- | <td style="background-color: #DEAFAF"></html>[[schedule#Scalable Machine Learning|Smola]]<html></td> | ||
- | <td style="background-color: #ffff00">Poster III</td> | ||
- | </tr> | ||
- | <tr> | ||
- | <td colspan="7" class="uk-text-center">Lunch Break</td> | ||
- | </tr> | ||
- | <tr> | ||
- | <td>13:30-15:00</td> | ||
- | <td style="background-color: #FAEBD7"></html>[[schedule#Convex Optimization|Boyd]]<html></td> | ||
- | <td style="background-color: #FAEBD7"></html>[[schedule#Convex Optimization|Boyd]]<html></td> | ||
- | <td style="background-color: #FFDAB9"></html>[[schedule#Submodular Functions|Jegelka]]<html></td> | ||
- | <td style="background-color: #FAA992"></html>[[schedule#Statistical and Computational Aspects of High-Dimensional Learning|Rigollet]]<html></td> | ||
- | <td style="background-color: #cf0000; color: #fff;" >Kyoto U.</td> | ||
- | <td style="background-color: #DEAFAF"></html>[[schedule#Scalable Machine Learning|Smola]]<html></td> | ||
- | </tr> | ||
- | <tr> | ||
- | <td>15:30-17:00</td> | ||
- | <td style="background-color: #ADD8E6"></html>[[schedule#Concentration Inequalities|Lugosi]]<html></td> | ||
- | <td style="background-color: #ADD8E6"></html>[[schedule#Concentration Inequalities|Lugosi]]<html></td> | ||
- | <td style="background-color: #FAA992"></html>[[schedule#Statistical and Computational Aspects of High-Dimensional Learning|Rigollet]]<html></td> | ||
- | <td style="background-color: #66DDFF"></html>[[schedule#Learning Representations|Rosasco]]<html></td> | ||
- | <td style="background-color: #ffff00" rowspan="2">Poster II<br>(-18:00)</td> | ||
- | <td style="background-color: #66DDFF"></html>[[schedule#Learning Representations|Rosasco]]<html></td> | ||
- | </tr> | ||
- | <tr> | ||
- | <td>17:30-19:00</td> | ||
- | <td style="background-color: #ADD8E6"></html>[[schedule#Concentration Inequalities|Lugosi]]<html></td> | ||
- | <td style="background-color: #3CB371"></html>[[schedule#Probabilistic Programming|De Raedt]]<html></td> | ||
- | <td style="background-color: #ffff00">Spotlights</td> | ||
- | <td style="background-color: #ffff00">Poster I</td> | ||
- | <td style="background-color: #66DDFF"></html>[[schedule#Learning Representations|Rosasco]]<html></td> | ||
- | </tr> | ||
- | <tr> | ||
- | <td></td><td></td><td></td><td></td><td></td> | ||
- | <td style="background-color: #00ccff">Karaoke Party</td> | ||
- | <td></td> | ||
- | </tr> | ||
- | </table> | ||
- | </html> | ||
- | <html> | + | ===== Registration and Opening Statements ===== |
- | <table class="uk-table uk-table-condensed"> | + | |
- | <tr> | + | |
- | <td style="width:100px;"></td> | + | |
- | <td></td> | + | |
- | <td style="width:100px;">Mon. 31st</td> | + | |
- | <td style="width:100px;">Tue. 1st</td> | + | |
- | <td style="width:100px;">Wed. 2nd</td> | + | |
- | <td style="width:100px;">Thu. 3rd</td> | + | |
- | <td style="width:100px;">Fri. 4th</td> | + | |
- | </tr> | + | Due to the large number of applicants, ** we will open the registration desk from 8:00 AM and encourage all participants to finish registration by 9:30**. |
- | <tr> | + | |
- | <td>8:30-10:00</td> | + | |
- | <td></td> | + | |
- | <td style="background-color: #FFE4E1"></html>[[schedule#Reinforcement Learning|Szepesvari]]<html></td> | + | |
- | <td style="background-color: #B0C4DE"></html>[[schedule#Machine Learning for Computer Vision|Harchaoui]]<html></td> | + | |
- | <td style="background-color: #DDA0DD"></html>[[schedule#Tensor Decompositions|Tomioka]]<html></td> | + | |
- | <td></td> | + | |
- | <td style="background-color: #8FBC8F"></html>[[schedule#Statistical Guarantees in Optimization|Wainwright]]<html></td> | + | |
- | </tr> | + | We will give opening remarks and announcements from 9:40 to 10:00 AM. |
- | <tr> | + | |
- | <td>10:30-12:00</td> | + | |
- | <td></td> | + | |
- | <td style="background-color: #FFE4E1"></html>[[schedule#Reinforcement Learning|Szepesvari]]<html></td> | + | |
- | <td style="background-color: #FFE4E1"></html>[[schedule#Reinforcement Learning|Szepesvari]]<html></td> | + | |
- | <td style="background-color: #99DDFF"></html>[[schedule#Stochastic Optimization|Suzuki]]<html></td> | + | |
- | <td style="background-color: #66CDAA"></html>[[schedule#Large Scale Deep Learning|Vanhoucke]]<html></td> | + | |
- | <td style="background-color: #8FBC8F"></html>[[schedule#Statistical Guarantees in Optimization|Wainwright]]<html></td> | + | |
- | </tr> | + | |
- | <tr> | + | |
- | <td colspan="7" class="uk-text-center">Lunch Break</td> | + | |
- | </tr> | + | |
- | <tr> | + | |
- | <td>13:30-15:00</td> | + | |
- | <td></td> | + | |
- | <td style="background-color: #B0C4DE"></html>[[schedule#Machine Learning for Computer Vision|Harchaoui]]<html></td> | + | |
- | <td style="background-color: #DDA0DD"></html>[[schedule#Tensor Decompositions|Tomioka]]<html></td> | + | |
- | <td style="background-color: #66CDAA"></html>[[schedule#Large Scale Deep Learning|Vanhoucke]]<html></td> | + | |
- | <td style="background-color: #8FBC8F"></html>[[schedule#Statistical Guarantees in Optimization|Wainwright]]<html></td> | + | |
- | <td style="background-color: #99DDFF"></html>[[schedule#Stochastic Optimization|Suzuki]]<html></td> | + | |
- | </tr> | + | |
- | <tr> | + | |
- | <td>15:30-17:00</td> | + | |
- | <td></td> | + | |
- | <td style="background-color: #B0C4DE"></html>[[schedule#Machine Learning for Computer Vision|Harchaoui]]<html></td> | + | |
- | <td style="background-color: #DDA0DD"></html>[[schedule#Tensor Decompositions|Tomioka]]<html></td> | + | |
- | <td style="background-color: #66CDAA"></html>[[schedule#Large Scale Deep Learning|Vanhoucke]]<html></td> | + | |
- | <td style="background-color: #99DDFF"></html>[[schedule#Stochastic Optimization|Suzuki]]<html></td> | + | |
- | <td></td> | + | |
- | </tr> | + | |
- | <tr> | + | |
- | <td>17:30-19:00</td> | + | |
- | <td></td> | + | |
- | <td></td> | + | |
- | <td style="background-color: #ffff00">Poster IV</td> | + | |
- | <td style="background-color: #00ccff" rowspan="2">Banquet</td> | + | |
- | <td style="background-color: #ffff00">Poster V</td> | + | |
- | <td></td> | + | |
- | </tr> | + | |
- | </table> | + | |
- | </html> | + | |
- | ===== Registration and Opening Statements ===== | + | ===== Lectures ===== |
- | + | ||
- | 多くの参加者が予想されるため,レジストレーションの時間帯(8:30am〜9:30am)を特別に設けています,早めに会場にお越しいただき,ご協力いただけると幸いです.またサマースクール開幕に先立ちまして,開催に関する注意事項等を説明する時間として9:40am頃から10:00am頃まで、オープニングトークを行います。 | + | |
- | + | ||
- | ===== 講義リスト ===== | + | |
==== Convex Optimization ==== | ==== Convex Optimization ==== | ||
- | ** [[http://stanford.edu/~boyd/|Stephen P. Boyd]], Stanford ** | + | [[http://stanford.edu/~boyd/|Stephen P. Boyd]], Stanford |
* [[https://www.dropbox.com/s/qs9n2gl8fnowwgx/cvx_about_course.pdf?dl=0| Introduction]] | * [[https://www.dropbox.com/s/qs9n2gl8fnowwgx/cvx_about_course.pdf?dl=0| Introduction]] | ||
* [[https://www.dropbox.com/s/hv8ae1jlubzij85/cvx_opt_intro.pdf?dl=0|Slides 1]] | * [[https://www.dropbox.com/s/hv8ae1jlubzij85/cvx_opt_intro.pdf?dl=0|Slides 1]] | ||
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* [[http://stanford.edu/~boyd/papers/cvx_short_course.html|CVX Short Course]] | * [[http://stanford.edu/~boyd/papers/cvx_short_course.html|CVX Short Course]] | ||
==== Concentration Inequalities ==== | ==== Concentration Inequalities ==== | ||
- | ** [[http://www.econ.upf.edu/~lugosi/|Gábor Lugosi]], Pompeu Fabra** | + | [[http://www.econ.upf.edu/~lugosi/|Gábor Lugosi]], Pompeu Fabra |
* [[https://www.dropbox.com/s/idyl2v0zc7sfos9/slides_lugosi.pdf?dl=0|Slides]] | * [[https://www.dropbox.com/s/idyl2v0zc7sfos9/slides_lugosi.pdf?dl=0|Slides]] | ||
==== Topics in Selective Inference ==== | ==== Topics in Selective Inference ==== | ||
- | ** [[http://statweb.stanford.edu/~candes/|Emmanuel Candès]], Stanford** | + | [[http://statweb.stanford.edu/~candes/|Emmanuel Candès]], Stanford |
*[[https://www.dropbox.com/s/t6q8nmfhgzp1z7b/MLSS_candes.pdf?dl=0|Slides 1]] | *[[https://www.dropbox.com/s/t6q8nmfhgzp1z7b/MLSS_candes.pdf?dl=0|Slides 1]] | ||
*[[https://www.dropbox.com/s/xs2knumkrzrbuk6/Kyoto_MLSS2.pdf?dl=0|Slides 2]] | *[[https://www.dropbox.com/s/xs2knumkrzrbuk6/Kyoto_MLSS2.pdf?dl=0|Slides 2]] | ||
==== Probabilistic Programming ==== | ==== Probabilistic Programming ==== | ||
- | ** [[http://people.cs.kuleuven.be/~luc.deraedt/|Luc De Raedt]], KU Leuven** | + | [[http://people.cs.kuleuven.be/~luc.deraedt/|Luc De Raedt]], KU Leuven |
*[[https://www.dropbox.com/s/lrsyl6fw3508y55/pptutorialmlss15.pdf?dl=0|Slides]] | *[[https://www.dropbox.com/s/lrsyl6fw3508y55/pptutorialmlss15.pdf?dl=0|Slides]] | ||
==== Submodular Functions ==== | ==== Submodular Functions ==== | ||
- | ** [[http://www.cs.berkeley.edu/~stefje/|Stefanie Jegelka]], MIT ** | + | [[http://www.cs.berkeley.edu/~stefje/|Stefanie Jegelka]], MIT |
*[[http://people.csail.mit.edu/stefje/mlss/kyoto_mlss_lecture1.pdf|Slides 1]] | *[[http://people.csail.mit.edu/stefje/mlss/kyoto_mlss_lecture1.pdf|Slides 1]] | ||
+ | *[[http://people.csail.mit.edu/stefje/mlss/kyoto_mlss_lecture2.pdf|Slides 2]] | ||
+ | *[[http://people.csail.mit.edu/stefje/mlss/kyoto_mlss_lecture3.pdf|Slides 3]] | ||
+ | *[[http://people.csail.mit.edu/stefje/mlss/literature.pdf|Literature]] | ||
+ | |||
==== Statistical and Computational Aspects of High-Dimensional Learning ==== | ==== Statistical and Computational Aspects of High-Dimensional Learning ==== | ||
- | ** [[http://math.mit.edu/directory/profile.php?pid=1654|Philippe Rigollet]], MIT ** | + | [[http://math.mit.edu/directory/profile.php?pid=1654|Philippe Rigollet]], MIT |
*[[https://www.dropbox.com/s/dhgamcmk1lp5c9d/MLSS15.pdf?dl=0|Slides]] | *[[https://www.dropbox.com/s/dhgamcmk1lp5c9d/MLSS15.pdf?dl=0|Slides]] | ||
==== Learning Representations ==== | ==== Learning Representations ==== | ||
- | ** [[http://web.mit.edu/lrosasco/www/|Lorenzo Rosasco]], MIT / Genoa** | + | [[http://web.mit.edu/lrosasco/www/|Lorenzo Rosasco]], MIT / Genoa |
*[[https://www.dropbox.com/sh/bzull20emgtyc6e/AAAkdnb4EYZPeGWlg-aD2CNra?dl=0|Slides]] | *[[https://www.dropbox.com/sh/bzull20emgtyc6e/AAAkdnb4EYZPeGWlg-aD2CNra?dl=0|Slides]] | ||
==== Scalable Machine Learning ==== | ==== Scalable Machine Learning ==== | ||
- | ** [[http://alex.smola.org/|Alexander J. Smola]], CMU** | + | [[http://alex.smola.org/|Alexander J. Smola]], CMU |
+ | *[[https://www.dropbox.com/s/t8k4rfw56y3r9o0/FastCheapDeep.pdf?dl=0|Slides]] | ||
==== Reinforcement Learning ==== | ==== Reinforcement Learning ==== | ||
- | ** [[http://www.ualberta.ca/~szepesva/|Csaba Szepesvári]], Alberta ** | + | [[http://www.ualberta.ca/~szepesva/|Csaba Szepesvári]], Alberta |
- | * [[https://dl.dropboxusercontent.com/u/6099418/MLSS2015-RL-Part1.pdf|Slides 1]] | + | * [[http://www.ualberta.ca/~szepesva/Talks/MLSS2015-RL-Part1.pdf|Slides 1]] |
- | * [[https://dl.dropboxusercontent.com/u/6099418/MLSS2015-RL-Part2.pdf|Slides 2]] | + | * [[http://www.ualberta.ca/~szepesva/Talks/MLSS2015-RL-Part2.pdf|Slides 2]] |
+ | * [[http://www.ualberta.ca/~szepesva/Talks/MLSS2015-RL-Part3.pdf|Slides 3]] | ||
==== Machine Learning for Computer Vision ==== | ==== Machine Learning for Computer Vision ==== | ||
- | ** [[http://www.harchaoui.eu/zaid/en/index.php|Zaid Harchaoui]], NYU/INRIA ** | + | [[http://www.harchaoui.eu/zaid/en/index.php|Zaid Harchaoui]], NYU/INRIA |
+ | * [[http://www.harchaoui.eu/zaid/share/2015/harch_mlss15_part1.pdf|Slides 1]] | ||
+ | * [[http://www.harchaoui.eu/zaid/share/2015/harch_mlss15_part2.pdf|Slides 2]] | ||
+ | * [[http://www.harchaoui.eu/zaid/share/2015/harch_mlss15_part3.pdf|Slides 3]] | ||
==== Tensor Decompositions ==== | ==== Tensor Decompositions ==== | ||
- | ** [[http://ttic.uchicago.edu/~ryotat/|Ryota Tomioka]], TTI Chicago** | + | [[http://ttic.uchicago.edu/~ryotat/|Ryota Tomioka]], TTI Chicago |
* [[https://github.com/ryotat/mlss15/blob/master/mlss15.pdf|Slides]] | * [[https://github.com/ryotat/mlss15/blob/master/mlss15.pdf|Slides]] | ||
==== Stochastic Optimization ==== | ==== Stochastic Optimization ==== | ||
- | ** [[http://www.is.titech.ac.jp/~s-taiji/|Taiji Suzuki]], Tokyo Tech** | + | [[http://www.is.titech.ac.jp/~s-taiji/|Taiji Suzuki]], Tokyo Tech |
* [[http://www.is.titech.ac.jp/~s-taiji/mlss2015/MLSS2015.pdf|Slides 1]] | * [[http://www.is.titech.ac.jp/~s-taiji/mlss2015/MLSS2015.pdf|Slides 1]] | ||
* [[http://www.is.titech.ac.jp/~s-taiji/mlss2015/MLSS2015_2.pdf|Slides 2]] | * [[http://www.is.titech.ac.jp/~s-taiji/mlss2015/MLSS2015_2.pdf|Slides 2]] | ||
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==== Large Scale Deep Learning ==== | ==== Large Scale Deep Learning ==== | ||
- | ** [[http://research.google.com/pubs/VincentVanhoucke.html|Vincent Vanhoucke]], | + | [[http://research.google.com/pubs/VincentVanhoucke.html|Vincent Vanhoucke]], |
- | Google ** | + | |
+ | * [[https://drive.google.com/file/d/0B525s-oGR9wpN1hWOGMyaE5pcXc/view?invite=CM2K7cQI|Slides]] | ||
==== Statistical Guarantees in Optimization ==== | ==== Statistical Guarantees in Optimization ==== | ||
- | ** [[http://www.cs.berkeley.edu/~wainwrig/|Martin Wainwright]], Berkeley** | + | [[http://www.cs.berkeley.edu/~wainwrig/|Martin Wainwright]], Berkeley |
* [[https://www.dropbox.com/s/d0ysjlioek0oln5/Wainwright_Lecture1.pdf?dl=0|Slides 1]] | * [[https://www.dropbox.com/s/d0ysjlioek0oln5/Wainwright_Lecture1.pdf?dl=0|Slides 1]] | ||
+ | * [[https://www.dropbox.com/s/mcjpiwaztcbx34i/Wainwright_Lecture2.pdf?dl=0|Slides 2]] | ||
+ | * [[https://www.dropbox.com/s/nsi6tr6f359px87/Wainwright_Lecture3.pdf?dl=0|Slides 3]] | ||
+ | |||
==== Kyoto U. Session ==== | ==== Kyoto U. Session ==== | ||
Location: 3rd floor of Building 4 of the south campus | Location: 3rd floor of Building 4 of the south campus |