MLSS 2015 Kyoto

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-===== 講義スケジュール ​=====+===== Schedule ​=====
  
-**開催日時8/23 (から 9/4(まで**+**DatesAugust 23rd (Sunto 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 **+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
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