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ol ol ol ol ol ol {list-style-type:lower-roman;}
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/* the 'a' is required for IE, otherwise it renders the whole tiddler in bold */
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* html .viewer pre {width:99%; padding:0 0 1em 0;}
.viewer {line-height:1.4em; padding-top:0.5em;}
.viewer .button {margin:0 0.25em; padding:0 0.25em;}
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.zoomer {font-size:1.1em; position:absolute; overflow:hidden;}
.zoomer div {padding:1em;}

* html #backstage {width:99%;}
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#backstageArea {display:none; position:relative; overflow: hidden; z-index:150; padding:0.3em 0.5em;}
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#backstageArea a {font-weight:bold; margin-left:0.5em; padding:0.3em 0.5em;}
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/***
StyleSheet for use when a translation requires any css style changes.
This StyleSheet can be used directly by languages such as Chinese, Japanese and Korean which need larger font sizes.
***/
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body {font-size:0.8em;}
#sidebarOptions {font-size:1.05em;}
#sidebarOptions a {font-style:normal;}
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/*{{{*/
@media print {
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#displayArea {margin: 1em 1em 0em;}
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}
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<!--{{{-->
<div class='header' macro='gradient vert [[ColorPalette::PrimaryLight]] [[ColorPalette::PrimaryMid]]'>
<div class='headerShadow'>
<span class='siteTitle' refresh='content' tiddler='SiteTitle'></span>&nbsp;
<span class='siteSubtitle' refresh='content' tiddler='SiteSubtitle'></span>
</div>
<div class='headerForeground'>
<span class='siteTitle' refresh='content' tiddler='SiteTitle'></span>&nbsp;
<span class='siteSubtitle' refresh='content' tiddler='SiteSubtitle'></span>
</div>
</div>
<div id='mainMenu' refresh='content' tiddler='MainMenu'></div>
<div id='sidebar'>
<div id='sidebarOptions' refresh='content' tiddler='SideBarOptions'></div>
<div id='sidebarTabs' refresh='content' force='true' tiddler='SideBarTabs'></div>
</div>
<div id='displayArea'>
<div id='messageArea'></div>
<div id='tiddlerDisplay'></div>
</div>
<!--}}}-->
<!--{{{-->
<div class='toolbar' macro='toolbar [[ToolbarCommands::ViewToolbar]]'></div>
<div class='title' macro='view title'></div>
<div class='subtitle'><span macro='view modifier link'></span>, <span macro='view modified date'></span> (<span macro='message views.wikified.createdPrompt'></span> <span macro='view created date'></span>)</div>
<div class='tagging' macro='tagging'></div>
<div class='tagged' macro='tags'></div>
<div class='viewer' macro='view text wikified'></div>
<div class='tagClear'></div>
<!--}}}-->
<!--{{{-->
<div class='toolbar' macro='toolbar [[ToolbarCommands::EditToolbar]]'></div>
<div class='title' macro='view title'></div>
<div class='editor' macro='edit title'></div>
<div macro='annotations'></div>
<div class='editor' macro='edit text'></div>
<div class='editor' macro='edit tags'></div><div class='editorFooter'><span macro='message views.editor.tagPrompt'></span><span macro='tagChooser excludeLists'></span></div>
<!--}}}-->
To get started with this blank [[TiddlyWiki]], you'll need to modify the following tiddlers:
* [[SiteTitle]] & [[SiteSubtitle]]: The title and subtitle of the site, as shown above (after saving, they will also appear in the browser title bar)
* [[MainMenu]]: The menu (usually on the left)
* [[DefaultTiddlers]]: Contains the names of the tiddlers that you want to appear when the TiddlyWiki is opened
You'll also need to enter your username for signing your edits: <<option txtUserName>>
These [[InterfaceOptions]] for customising [[TiddlyWiki]] are saved in your browser

Your username for signing your edits. Write it as a [[WikiWord]] (eg [[JoeBloggs]])

<<option txtUserName>>
<<option chkSaveBackups>> [[SaveBackups]]
<<option chkAutoSave>> [[AutoSave]]
<<option chkRegExpSearch>> [[RegExpSearch]]
<<option chkCaseSensitiveSearch>> [[CaseSensitiveSearch]]
<<option chkAnimate>> [[EnableAnimations]]

----
Also see [[AdvancedOptions]]
<<importTiddlers>>
!!!Spring
|[[SDM|https://www.siam.org/activity/dma/]]|[[AISTATS|http://www.aistats.org/]]|[[PAKDD|http://pakdd.org]]|
!!!Summer
|[[SIGIR|http://sigir.org/]]|[[IJCAI|https://www.ijcai.org/]]|[[ICML|https://icml.nips.cc]]|[[KDD|http://www.kdd.org/]]|
!!!Fall
|[[ECML|http://www.ecmlpkdd.org/]]|[[ACML|http://www.acml-conf.org/]]|[[CIKM|http://cikmconference.org/]]|
!!!Winter
|[[NIPS|http://nips.cc/]]|[[ICDM|http://www.cs.uvm.edu/~icdm/]]|[[WSDM|http://www.wsdm-conference.org/]]|[[AAAI|http://www.aaai.org/Conferences/AAAI/]]|
!!!H-5 Index (Google Scholar)
[[Data Mining and Analysis|https://scholar.google.es/citations?view_op=top_venues&hl=en&vq=eng_datamininganalysis]]
[[Artificial Intelligence|https://scholar.google.es/citations?view_op=top_venues&hl=en&vq=eng_artificialintelligence]]
!!! Web of Science (Impact Factor)
[[Journal Citation Report|http://jcr.incites.thomsonreuters.com/JCRJournalHomeAction.action]]
;Tokyo University of Science
;School of Management
;Department of Business Economics
;Associate Professor
----
;東京理科大学
;経営学部
;ビジネスエコノミクス学科
----
[[GoogleScholar|https://scholar.google.co.jp/citations?user=PX1xmOoAAAAJ&hl=en]]
[[ORCID|http://orcid.org/0000-0002-4822-2804]]
[[DBLP|http://www.informatik.uni-trier.de/~ley/db/indices/a-tree/a/Ando:Shin.html]]
[[CINII|http://ci.nii.ac.jp/author?q=%E5%AE%89%E8%97%A4%E6%99%8B]]
[[ACM Porta (2011-)|http://dl.acm.org/author_page.cfm?id=81496655150]] [[(2002-2011)|http://dl.acm.org/author_page.cfm?id=81100486044]]
[[IEEE CS Digital Library|http://search3.computer.org/search/results?action=authorsearch&resultsPerPage=50&queryOption1=DC_CREATOR&sortOrder=descending&queryText1=Shin%20Ando]]
[img[MS_small.jpg|MS_small.jpg]]

! Research Interests
Shin Ando is an Associate Professor at the School of Management in Tokyo University Science starting 2016. His research focuses on extracting knowledge from anomalous and exceptional data. He is broadly interested in questions related to data mining, machine learning and artificial intelligence. 
! Eucation
Ph. D. in Electronics Engineering (2004)
Department of Electronics Engineering, School of Engineering, University of Tokyo

M.E. in Information and Communication Engineering (2001)
Department of Information and Communication Engineering, School of Engineering, University of Tokyo

B.E. in Information and Communication Engineering (1999)
Department of Information and Communication Engineering, Faculty of Engineering, University of Tokyo 

!Awards
2004 Japanese Artificial Intelligence Society Best Paper Award 

!Selected Publications
*Shin Ando and , """"Discriminative Prototype Set Learning for Nearest Neighbor Learning"""," In Proceedings of 2018 SIAM International Conference on Data Mining pp.468-476 (DOI:[[10.1137/1.9781611975321.53|http://dx.doi.org/10.1137/1.9781611975321.53]]) [[PDF|http://epubs.siam.org/doi/pdf/10.1137/1.9781611975321.53]] 
*Shin Ando, """Chun-Yuan Huang"""; "Deep Over-sampling Framework for Classifying Imbalanced Data," in Machine Learning and Knowledge Discovery in Databases (LNCS 10534), Springer, 2017, 770-785  (DOI:[[10.1007/978-3-319-71249-9_46|https://doi.org/10.1007/978-3-319-71249-9_46]]) 
*Shin Ando, "Classifying Imbalanced Data in Distance-based Feature Space," //Knowledge and Information Systems//, 46, 707-730 (2015),  (DOI:[[10.1007/s10115-015-0846-3|http://dx.doi.org/10.1007/s10115-015-0846-3]]) [[readcube|http://rdcu.be/mTvG]]
*Shin Ando and Einoshin Suzuki, "Minimizing Response Time in Time Series Classification," //Knowledge and Information Systems//, 42, 449-476 (2015),  (DOI:[[10.1007/s10115-015-0826-7|http://dx.doi.org/10.1007/s10115-015-0826-7]]) [[readcube|http://rdcu.be/mTv2]]
*Shin Ando, Theerasak Thanomphongphan, Youichi Seki, Einoshin Suzuki, "Ensemble Anomaly Detection from Multi-resolution Trajectory Features," //Data Mining and Knowledge Discovery//, Volume 29, Issue 1 (2015), Page 39-83 (DOI:[[10.1007/s10618-013-0334-x|http://dx.doi.org/10.1007/s10618-013-0334-x]]) [[readcube|http://rdcu.be/mTwg]]
*Shin Ando and Einoshin Suzuki, "Discriminative Learning on Exemplary Patterns in Sequential Numerical Data," In Proceedings of the 2014 IEEE International Conference on Data Mining (ICDM), pp.1-10, 2014 [[DOI|http://dx.doi.org/10.1109/ICDM.2014.122|]] 
*Shin Ando and Einoshin Suzuki, """"Time-Sensitive""" Classification of Behavioral Data," In Proceedings of 2013 SIAM International Conference on Data Mining pp.458-466 (DOI:[[10.1137/1.9781611972832.51|http://dx.doi.org/10.1137/1.9781611972832.51]]) [[PDF|http://epubs.siam.org/doi/pdf/10.1137/1.9781611972832.51]] 
*Shin Ando, """Performance-Optimizing""" Classification of Time-series based on Nearest Neighbor Density Approximation, In """SSTDM-12""", IEEE 12th International Conference on Data Mining Workshops (ICDMW), 2012  (DOI:[[10.1109/ICDMW.2012.14|http://dx.doi.org/10.1109/ICDMW.2012.14]]). 
*Shin Ando and Einoshin Suzuki,"Role-behavior Analysis from Trajectory Data by Cross-domain Learning", in Procs. of Data Mining (ICDM), 2011 IEEE 11th International Conference on, pp.21-30, 2011 (DOI:[[10.1109/ICDM.2011.125|http://dx.doi.org/10.1109/ICDM.2011.125]])
*Shin Ando, "Latent Feature Encoding using Dyadic and Relational Data", in Proceedings of the 20th ACM International Conference on Information and Knowledge Management, pp.2201-2204, 2011 (DOI:[[10.1145/2063576.2063926|http://dx.doi.org/10.1145/2063576.2063926]])
* Shin Ando, Theerasak Tanomphongphan,  Daisuke Hoshino, Youichi Seki, and Einoshin Suzuki; "ACE: Anomaly Clustering Ensemble for Multi-perspective Anomaly Detection in Robot Behaviors," in Proceedings of 2011 SIAM International Conference on Data Mining ([[DOI:10.1137/1.9781611972818.1|http://dx.doi.org/10.1137/1.9781611972818.1]]), pp.55-68, 2011.  [[PDF|http://siam.omnibooksonline.com/data/papers/055.pdf#page=1]] ) 
* Shin Ando and Einoshin Suzuki, "Detection of Unique Temporal Segments by Information Theoretic Meta-clustering" in Proceedings of the 15th ACM SIGKDD Conference on Knowledge Discovery and Data Mining ("""KDD-09"""), pp.59-68, 2009. (DOI:[[10.1145/1557019.1557033|http://doi.acm.org/10.1145/1557019.1557033]]) 
* Shin Ando and Einoshin Suzuki, "Unsupervised Cross-domain Learning by Interaction Information Co-clustering," in Proceedings of 8th IEEE International Conference on Data Mining (~ICDM08), pp. 13-22, 2008. [[Abstract|http://doi.ieeecomputersociety.org/10.1109/ICDM.2008.92]]
*Shin Ando "Clustering Needles in a Haystack: An Information Theoretic Analysis of Minority and Outlier Detection," in Proceedings of 7th IEEE International Conference on Data Mining (ICDM'07), pp. 13-22, 2007. [[Abstract|http://doi.ieeecomputersociety.org/10.1109/ICDM.2007.53]]
* Shin Ando "Heuristic Speciation for Evolving Neural Network Ensembles", in Proceedings of 2007 Genetic and Evolutionary Computation ~COnference (GECCO 2007), pp. 1766-1773, ACM Press, 2007. [[Abstract|http://doi.acm.org/10.1145/1276958.1277315]]
* Shin Ando and Einoshin Suzuki, "An Information Theoretic Approach to Detection of Minority Subsets in Database", in Proceedings of the 6th International Conference on Data Mining (ICDM'06), pp. 11-20, 2006. [[Abstract|http://doi.ieeecomputersociety.org/10.1109/ICDM.2006.19]]
* Shin Ando, Jun Sakuma, and Shigenobu Kobayashi, "Adaptive isolation model using data clustering for multimodal function optimization" in Proceedings of the 2005 Genetic and Evolutionary Computation ~COnference (~GECCO2005), pp. 1417-1424, 2005. [[Abstract|http://doi.acm.org/10.1145/1068009.1068235]]
* Shin Ando, Hitoshi Iba,"Classification of Gene Expression Profile Using Combinatory Method of Evolutionary Computation and Machine Learning", ed.Wolfgang Banzhaf, Vol. 5, pp. 145-156, Genetic Programming and Evolvable Machines, Kluwer Publishing, 2004 [[Abstract|http://dx.doi.org/10.1023/B:GENP.0000023685.83861.69]]
* Shin Ando, Hitoshi Iba,"Variable Length Chromosomes for Analog Evolvable Hardware",eds. A Ghosh and S Tsutsui, Advances in Evolutionary Computation, pp. 643-662, ~Springer-Verlag, 2003 [[Abstract|http://dx.doi.org/10.1007/978-3-642-18965-4_25]]
* Shin Ando, Hitoshi Iba,"Construction of Genetic Network using Evolutionary Algorithm and Combined Fitness Function" Genome Informatics, 14: 94-103, 2002  [[Abstract|http://www.ncbi.nlm.nih.gov/pubmed/15706524]] [[PDF|http://www.ncbi.nlm.nih.gov/pubmed/15706524]] 
* Shin Ando, Hitoshi Iba,"Evolutionary Modeling and Inference by Genetic Network" Information Science, Vol. 145, Iss. 3-4, Elsevier Science 2001 [[Abstract|http://dx.doi.org/10.1016/S0020-0255(02)00235-9]] 


! Invited Talk
Mining Time Series and Subsequences (in Japanese), the 8th IBISML Workshop, March 2012.

! Teaching
Introduction to Data Science, School of Management, Tokyo University of Science 
Pattern Recognition, School of Management, Tokyo University of Science 
Big Data Analysis, School of Management, Tokyo University of Science 

! Service
;PC Member
ACM International Conference on Knowledge Discovery from Data (SIGKDD)
European Conference on Machine Learning and Principles of Knowledge Discovery from Data (ECML)
IEEE International Conference on Data Minimg (ICDM)
AAAI Conference
ACM Conference on Information and Knowledge Management (CIKM)
IEEE Congress on Evolutionary Computation (CEC)
Asian Conference on Machine Learning (ACML)
Workshop on LEarning and MIning from Robots (LEMIR)

;Reviewer
International Conference on Pattern Recognition
Knowledge and Information Systems Springer
Data Mining and Knowledge Discovery Springer

!Professional Experience
;2002-2003
Research Assistant for 21st Century COE 
Department of Electronics Engineering, School of Engineering, University of Tokyo
;2003-2004
Post Doctoral Researcher of Japanese Society for Promotion of Science 
Interdiciplanary Graduate School of Frontier Science,  University of Tokyo
;2004-2005
Post Doctoral Researcher of Japanese Society for Promotion of Science 
Interdiciplanary Graduate School of Science and Engineering, Tokyo Institute of Techonology
;2005-2008
Research Associate 
Faculty of Engineering, Yokohama National University
;2008-2013
Assistant Professor 
Faculty of Engineering, Gunma University
;2014-2016
Senior Lecturer, School of Management, Tokyo University of Science
;2016-
Associate Professor, School of Management, Tokyo University of Science

Type the text for 'New Tiddler'![[ECAI|http://ecai2010.appia.pt/index.php]]
-Deadline for electronic abstracts	Monday,	15 February 2010
-Paper submission deadline	Monday,	22 February 2010
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<img src="http://ecai2010.appia.pt/templates/ja_mercury/images/logo-default.jpg">
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![[WCCI2010|http://www.wcci2010.org]]
-January 31, 2010 Paper submission
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<img src="http://www.wcci2010.org/templates/jp_business/images/white/logo.gif" height="50pt">
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![[ICML2010|http://www.icml2010.org/]]
-February 1, 2010 Full paper submissions due
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<img src="http://www.icml2010.org/images/icml_banner.gif" height="50pt">
</html>

![[KDD2010|http://www.sigkdd.org/kdd2010/]]
-Feb 5, 2010  	Full Paper deadline
-Feb 2, 2010 	Paper abstract deadline
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<img src="http://www.kdd.org/kdd2010/images/KDD2010Banner__Final.jpg" height="50pt">
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![[ECML/PKDD2010|http://www.ecmlpkdd2010.org/]]
- Abstract submission deadline 23rd of April 2010
- Paper submission deadline 30th of April 2010
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<img src="http://www.ecmlpkdd2010.org/img/3629-200-0-IMG_ACCIO_SEE-eng.jpg" height="50pt">
</html>

![[CIKM2010|http://www.yorku.ca/cikm10/]]
- Abstracts due: May 27, 2010
- Papers due: June 3, 2010
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<img src="http://www.yorku.ca/cikm10/images/header.jpg" height="50pt">
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![[ICDM2010|http://datamining.it.uts.edu.au/icdm10/ICDM10-CFP-V1.txt]]
-Jul 02, 2010:   Deadline for full paper submission

![[SIGIR2010|http://www.sigir2010.org/doku.php]]
-15 Jan 2010 : Abstracts for full research papers due
-22 Jan 2010 : Full research paper submissions due
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<img src="http://www.sigir2010.org/lib/tpl/dokucms/images/sigir_150_transp.png" height="50pt">
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![[SDM2010|http://www.siam.org/meetings/sdm10/]]
- April 29 - May 1 2010 
<html>
<img src="http://www.siam.org/meetings/sdm10/images/sdmlogo.jpg" height="50pt">
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!ACML 2009
*The First Asian Conference on Machine Learning will be held in Nanjing, China, on Nov. 2-4, 2009
*For more details, see the [[conference website|http://lamda.nju.edu.cn/conf/ACML09/]].
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<img src="http://lamda.nju.edu.cn/conf/acml09/images/ACML.png" height="50pt">
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|Conference|abst|paper|auth. fb|notice|conf|
|*[[SIGIR|http://www.sigir2011.org/]]|1/17|1/24|-|4/8|7/24|
|*[[IJCAI|http://ijcai-11.iiia.csic.es/]]|1/19|1/25|2/28|3/31|7/19|
|*[[ICML|http://www.icml-2011.org/]]|-|2/1|3/25|4/19|6/27|
|*[[KDD|http://kdd.org/kdd/2011/]]|2/11|2/18|-|4/29|8/21|
|[[UAI|http://auai.org/uai2011/]]|-|3/18|4/29|5/5|7/14|
|*[[ECML|http://www.ecmlpkdd2011.org/]]|4/12|4/19|5/23|6/3|9/5|
|[[DS|http://ds2011.org/]]|-|5/18|-|6/30|10/5|
|~[[CIKM|http://www.cikm2011.org/]]|5/17|5/24|-|7/19|10/24|
|~[[NIPS|http://nips.cc/Conferences/2011/]]|-|6/2|7/31|9/3|12/13|
|~[[ICDM|http://icdm2011.cs.ualberta.ca/]]|-|6/17|-|9/16|12/11|
|[[ACML|http://acml2011.ncu.edu.tw/]]|7/11|7/19|-|9/6|11/13|
|[[ICDE|http://www.icde12.org/Site/]]|7/12|7/19|9/8|9/27|+4/1|
|[[WSDM|http://wsdm2012.org]]|8/4|8/11|-|10/26|+2/8|
|*[[PAKDD|http://pakdd2012.pakdd.org/]]||10/2|-|12/30|+5/29|
|[[ECIR|http://ecir2012.upf.edu]]|-|10/2|-|11/27|+4/1|
|[[AISTAT|http://www.aistats.org]]|-|10/14|11/25|12/12|+4/21|
|*[[SDM|http://www.siam.org/meetings/sdm12/]]|-|10/14|-|12/21|+4/26|
|[[SIGMOD|http://www.sigmod.org/2012/]]|10/25|11/1|+1/19|+2/14|+5/20|
|[[WWW|http://www2012.org/]]|11/1|11/7|-|+1/30|+4/16|
|name|abst|paper|feedback|notice|conf|site|
|[[*KDD|http://kdd.org/kdd2012/]]|-|2/10|-|5/4|8/16|Beijing,CN|
|[[*SIGIR|http://www.sigir.org/sigir2012/]]|2/6|2/13|-|4/30|8/12|Portland,OR|
|[[*ICML|http://icml.cc/2012/]]|-|2/24|4/9|4/30|7/25|Edinburgh,UK|
|[[*ECML|http://www.ecmlpkdd2012.net/]]|4/19|4/23|5/28|6/15|9/24|Bristol,UK|
|[[*CIKM|http://www.cikm2012.org]]|5/18|5/25|-|7/16|10/29|Maui, HI|
|[[*NIPS|http://nips.cc]]|-|6/1|-|-|12/3|Lake Tahoe, NV|
|[[*ICDM|http://icdm2012.ua.ac.be/]]|-|6/18|-|9/18|12/18|Brussels,BE|
|[[*ICDE|http://www.icde2013.org]]|7/16|7/23|-|10/14|+4/8|Brisbane, AU|
|[[*ACML|http://acml12.comp.nus.edu.sg/]]|-|7/24|-|9/8|11/4|Singapore|
|[[*SAC|http://www.acm.org/conferences/sac/sac2013/]]|-|8/13|-|-|+5/18|Coimbra, PT|
|[[PAKDD|http://pakdd2013.pakdd.org/]]|-|10/1|-|12/19|+4/14|Gold Coast, AU|
|[[SDM|http://www.siam.org/meetings/sdm13]]|-|10/12|-|12/20|+5/2|Austin, TX|
|[[AISTAT|http://www.aistats.org]]|-|11/15|-|-|+4/29|Scottsdale, AZ|
|[[WWW|http://www2013.wwwconference.org/conferences/]]|11/19|11/26|-|+2/8|+5/13|Rio, BR|
|name|abst|paper|feedback|notice|conf|site|
|[[SIGIR|http://sigir2013.ie/]]|1/21|1/28|-|4/15|7/28|Dublin,IR|
|[[ICML|http://icml.cc/2013/]]|-|*2/15|3/15|4/15|7/16|Atlanta,GA|
|[[IJCAI|http://ijcai13.org/]]|1/26|1/31|3/4|-|8/5|Beijing,CN|
|[[KDD|http://www.kdd.org/kdd2013]]|2/15|2/22|-|5/3|8/11|Chicago,IL|
|[[ECML|http://www.ecmlpkdd2013.org/]]|4/18|4/22|-|6/14|9/23|Prague,CZ|
|[[CIKM|http://www.cikm2013.org]]|5/10|5/17|-|7/15|10/27|San Francisco, CA|
|[[ICDM|http://icdm2013.rutgers.edu/]]|-|6/21|-|9/20|12/8|Dallas, TX|
|[[NIPS|http://nips.cc/]]|-|7/15|-|9/5|12/5|Lake Tahoe, NV|
|[[PAKDD|http://pakdd2014.pakdd.org/]]|-|9/16|-|12/20|+5/13|Tainan, TW|
|[[SDM|http://www.siam.org/meetings/sdm14]]|10/6|10/13|-|12/16|+4/24|Philadelphia, PA|
|[[WWW|http://www2014.wwwconference.org/conferences/]]|-|10/8|-|+1/4|+4/7|Seoul, KR|
|[[AISTAT|http://www.aistats.org]]|-|11/1|12/17|+1/20|+4/22|Reykjavik, IS|
|name|abst|paper|feedback|notice|conf|site|
|[[SIGIR|sigir.org/sigir2014/]]|1/20|1/27|-|4/18|7/6|Gold Coast,AU|
|[[ICML|http://icml.cc/2014/]]|-|1/31|3/16|4/9|7/22|Beijing,CN|
|[[KDD|http://www.kdd.org/kdd2014]]|2/14|2/21|-|5/14|8/11|New York, NY|
|[[ECML|http://www.ecmlpkdd2014.org/]]|4/12|4/16|-|6/9|9/15|Nancy,FR|
|[[CIKM|http://cikm2014.fudan.edu.cn/]]|6/4|6/11|7/21|8/8|11/3|Shanghai, CN|
|[[ICDM|http://icdm2014.sfu.ca/home.html]]|-|6/24|-|9/24|12/14|Shenzhen, CN|
|[[NIPS|http://nips.cc/]]|-|6/6|-|-|12/8|Montreal, CA|
|[[SDM|http://www.siam.org/meetings/sdm15]]|10/5|10/12|-|12/22|+4/30|Vancouver, CA|
|[[AISTATS|http://www.aistats.org/dates.php]]||10/24|12/8|12/23|+5/10|San Diego, CA|
|[[PAKDD|http://pakdd2015.pakdd.org]]|-|11/28|-|1/30|+5/19|Ho Chi Minh City,VN|
|[[WWW|http://www.www2015.it/]]|11/3|11/10|-|+1/17|+5/18|Florence, IT|
|name|abst|paper|feedback|notice|conf|site|
|[[SIGIR|http://sigir.org/sigir2015/]]|1/21|1/28|-|4/20|8/9|Santiago, CL|
|[[IJCAI|http://ijcai-15.org/]]|2/1|2/5|3/10|4/9|7/25|Buenos Aires, AR|
|[[ICML|http://icml.cc/2015/]]|-|2/6|3/30|4/24|7/6|Lille,FR|
|[[KDD|http://www.kdd.org/kdd2015]]|-|2/20|-|5/12|8/10|Sydney, AU|
|[[VLDB|http://vldb.org/2015/]]|-|2/28|-|-|8/31|Kohala Coast, HI|
|[[ECML|http://www.ecmlpkdd2015.org/]]|3/26|4/2|-|6/1|9/7|Porto, PT|
|[[CIKM|http://www.cikm-2015.org]]|5/1|5/8|-|7/3|10/19|Melbourne, AU|
|[[ICDM|http://icdm2015.stonybrook.edu]]|-|6/3|-|8/7|11/14|Atlantic City, NJ|
|[[NIPS|http://nips.cc/]]|-|6/5|-|9/4|12/7|Montreal, CA|
|name|abst|paper|feedback|notice|conf|site|
|[[PAKDD|http://pakdd2016.pakdd.org]]|-|*10/2|-|*12/11|4/19|Auckland, NZ|
|[[AISTATS|http://www.aistats.org/]]|-|*10/9|*11/23|*12/20|5/9|Cadiz, ES|
|[[SDM|http://www.siam.org/meetings/sdm16]]|*10/9|*10/16|-|*12/21|5/5|Miami, FL||[[SIGIR|http://sigir.org/sigir2016/]]|1/14|1/21|-|3/31|7/18|Pisa, IT|
|[[IJCAI|http://ijcai-16.org/]]|1/27|2/2|3/10|4/4|7/9|New York City, NY|
|[[ICML|http://icml.cc/2016/]]|-|2/5|3/25|-|6/19|New York City, NY|
|[[KDD|http://www.kdd.org/kdd2016]]|-|2/12|-|5/12|8/24|San Francisco, CA|
|[[ECML|http://www.ecmlpkdd2016.org/]]|4/1|4/4|-|6/20|9/7|Riva del Garda, IT|
|[[ACML|http://www.acml-conf.org/2016/]]|-|5/9,8/15|6/20,9/26|-|11/16|Hamilton, NZ|
|[[CIKM|http://www.cikm2016.org/]]|5/9|5/16|-|7/18|10/24|Indianapolis, IN|
|[[NIPS|http://nips.cc/]]|-|5/20|-|-|12/5|Barcelona, ES|
|[[ICDM|http://icdm2016.eurecat.org/]]|-|6/17|-|9/9|12/13|Barcelona, ES|
|[[WSDM|http://www.wsdm-conference.org/]]|7/31|8/7|-|10/24|+2/6|Cambridge, UK|
|name|abst|paper|feedback|notice|conf|site|
|[[SDM|http://www.siam.org/meetings/sdm17]]|*10/8|*10/15|-|*12/19|4/17|Houston, TX|
|[[AISTATS|http://www.aistats.org/]]|-|*10/13|*12/9|1/24|4/20|Fort Laudardale, FL|
|[[PAKDD|http://pakdd2017.snu.ac.kr]]|-|*10/30|-|1/13|5/23|Jeju, KR|
|[[SIGIR|http://sigir.org/sigir2017/]]|1/17|1/24|-|4/11|8/10|Tokyo, JP|
|[[IJCAI|http://ijcai-17.org/]]|-|2/19|-|4/23|8/19|Melbourne, AU|
|[[ICML|https://icml.nips.cc]]|-|2/24|4/14|5/12|8/6|Sydney, AU|
|[[KDD|http://www.kdd.org/kdd2017]]|-|2/17|-|5/19|8/13|Halifax, CA|
|[[ECML|http://ecmlpkdd2017.ijs.si]]|4/13|4/20|6/1|6/22|9/19|Skopje, FYROM|
|[[ACML|http://www.acml-conf.org/]]|5/10'|8/5|6/20'|9/15|11/15|Seoul, KR|
|[[CIKM|http://www.cikm2017.org]]|5/16|5/23|-|8/6|11/6|Singapore|
|[[NIPS|http://nips.cc/]]|-|5/19|-|-|12/4|Long Beach, CA|
|[[ICDM|http://icdm2017.bigke.org/]]|-|6/5|-|8/15|11/18|New Orleans, LA|
|[[WSDM|http://www.wsdm-conference.org/2018/]]|8/4|8/12|-|10/23|2/6|Los Angeles, CA|
|[[AAAI|www.aaai.org/Conferences/AAAI/aaai18.php]]|9/8|9/11|10/16|11/9|2/2|New Orleans, LA|
|name|abst|paper|feedback|notice|conf|site|
|[[SDM|http://www.siam.org/meetings/sdm18]]|*10/6|*10/13|-|*12/19|5/3|San Diego, CA|
|[[AISTATS|http://www.aistats.org/]]|-|*10/13|*11/29|*12/22|4/9|Lanzarote, ES|
|[[PAKDD|http://prada-research.net/pakdd18/]]|-|*10/31|-|1/28|6/3|Melbourne, AU|
|[[SIGIR|http://sigir.org/sigir2018/]]|1/22|1/29|-|-|7/8|Ann Arbor, MI|
|[[IJCAI|http://www.ijcai-18.org/]]|-|1/31|-|4/16|7/13|Stockholm, SE|
|[[ICML|https://icml.nips.cc/Conferences/2018]]|-|2/9|4/11|5/11|7/10|Stockholm, SE|
|[[KDD|http://www.kdd.org/kdd2018/]]|-|2/11|-|5/6|8/19|London, UK|
|[[ECMLPKDD|http://www.ecmlpkdd2018.org/]]|4/5|4/12|-|6/14|9/10|Dublin,IR|
|[[CIKM|http://www.cikm2018.units.it]]|5/15|5/22|-|8/6|10/22|Turin, IT|
|[[NIPS|http://nips.cc/]]|-|5/18|-|-|12/3|Montreal, CA|
|[[ICDM|http://icdm2018.org]]|-|6/5|-|8/17|11/17|Singapore|
|[[WSDM|http://www.wsdm-conference.org/2019/]]|8/8|8/15|-|10/24|2/11|Melbourne, AU|
|[[AAAI|https://aaai.org/Conferences/AAAI-19/]]|9/1|9/5|10/11|11/1|1/27|Honolulu,HI|
|name|abst|paper|feedback|notice|conf|site|
|[[SDM|http://www.siam.org/meetings/sdm19]]|-|*10/12|-|1/15|5/2|Calgary, CA|
|[[PAKDD|http://pakdd2019.medmeeting.org/Content/92892]]|-|*10/17|-|*12/15|4/14|Macau, CN|
|[[AISTATS|http://www.aistats.org/]]|-|*10/4|*11/21|*12/24|4/16|Naha, JP|
|[[IJCNN|https://www.ijcnn.org]]|-|1/15|-|3/8|7/14|Budapest, HU|
|[[ICML|https://icml.nips.cc/Conferences/2019]]|1/18|1/23|-|-|6/10|Long Beach, CA|
|[[SIGIR|http://sigir.org/sigir2019/]]|1/21|1/28|-|4/14|7/21|Paris, FR|
|[[KDD|http://www.kdd.org/kdd2019/]]|-|2/11|-|5/6|8/19|Anchorage, AK|
|[[IJCAI|http://ijcai19.org]]|2/19|2/25|4/13|5/9|8/10|Macao, CN|
|[[CIKM|http://www.cikm2019.net]]|3/15|3/22|-|8/6|11/3|Beijing, CN|
|[[ECMLPKDD|http://www.ecmlpkdd2019.org/]]|3/29|4/5|-|6/7|9/16|Würzburg, DE|
|[[NeurIPS|http://nips.cc/Conferences/2019]]|-|5/23|-|-|12/8|Vancouver, CA|
|[[ICDM|http://icdm2019.bigke.org]]|-|6/5|-|8/8|11/8|Beijing, CN|
|[[WSDM|http://www.wsdm-conference.org/2020/]]|8/12|8/16|-|10/24|*2/5|Houston, TX|
|[[AAAI|https://aaai.org/Conferences/AAAI-20/]]|8/30|9/5|10/10|11/10|*2/7|NYC|
|[[IEEEBigData|http://bigdataieee.org/BigData2019]]|-|8/19||10/16|12/9|NYC|
|[[ICMLA|https://www.icmla-conference.org/icmla19/]]|-|7/5|-|8/31|12/16|Boca Raton,FL|
|name|abst|paper|feedback|notice|conf|site|
|[[SDM|https://www.siam.org/Conferences/CM/Conference/sdm20]]|*10/4|*10/11|-|*12/x|5/7|Cincinnati, OH|
|[[AISTATS|http://www.aistats.org/]]|-|*10/8|*11/25|1/6|6/3|Palermo, IT|
|[[ECAI|http://ecai2020.eu/]]|*11/15|*11/19|*12/18|1/15|6/8|Santiago de Compostela, ES|
|[[PAKDD|https://www.pakdd2020.org/]]|*11/18|*11/25|-|1/28|5/11|Singapore|
|[[WCCI|https://wcci2020.org]]|-|1/15|-|3/15|7/19|Glasgow, UK|
|[[IJCAI|http://ijcai20.org]]|1/15|1/21|3/21|4/19|7/11|Yokohama, JP|
|[[SIGIR|http://sigir.org/sigir2020/]]|1/15|1/22|-|4/22|6/25|Xi'an, CN|
|[[ICML|https://icml.nips.cc/Conferences/2020]]|1/31|2/7|4/1|5/9|7/14|Vienna, AT|
|[[KDD|http://www.kdd.org/kdd2020/]]|-|2/13|-|5/15|8/22|San Diego, CA|
|[[ECMLPKDD|http://ecmlpkdd2020.net/]]|3/19|3/26|-|6/4|9/18|Ghent, BE|
|[[ICANN|https://e-nns.org/icann2020/]]|3/15|3/15|-|5/1|9/15|Bratislava, SK|
|[[CIKM|http://cikm2020.org]]|4/24|5/1|-|7/3|10/19|Galway, IR|
|[[ICDM|http://icdm2020.bigke.org/]]|-|6/2|-|8/20|11/17|Sorrento, IT|
|name|abst|paper|feedback|notice|conf|site|
|[[SDM|https://www.siam.org/Conferences/CM/Conference/sdm21]]|-|*10/12|-|1/x|4/29|Virtual Online|
|[[AISTATS|http://www.aistats.org/]]|*10/8|*10/15|*12/2|1/22|4/13|Virtual Online|
|[[PAKDD|https://www.pakdd2021.org/]]|*12/7|*12/7|-|2/8|5/11|Virtual Online|
|[[IJCAI|http://ijcai-21.org]]|1/13|1/20|3/24|4/30|8/21|Montreal, CA|
|[[ICML|https://icml.nips.cc/Conferences/2021]]|1/28|2/4|-|-|7/18|Virtual Online|
|[[KDD|http://www.kdd.org/kdd2021/]]|-|2/8|-|-|8/14|Virtual Online|
|[[SIGIR|http://sigir.org/sigir2021/]]|2/2|2/9|-|4/14|7/11|Virtual Online|
|[[IJCNN|https://www.ijcnn.org/]]|-|2/10|-|3/15|7/18|Virtual Online|
|[[ICANN|https://e-nns.org/icann2021/]]|-|3/15|-|5/1|9/14|TBA|
|[[ECMLPKDD|http://2021.ecmlpkdd.org]]|3/26|4/2|-|6/18|9/13|Virtual Online|
|[[CIKM|http://cikm2021.org]]|-|TBA|-|-|11/1|Gold Coast, AU|
|[[ICDM|https://icdm2021.auckland.ac.nz]]|-|6/11|-|9/24|12/7|Auckland, NZ|
|[[ICPRAM|http://www.icpram.org/]]|-|9/14|-|11/15|2/3|Vienna, Austria|
Address: 1-11-2  Fujimi, Chiyoda-ku, Tokyo, 102-0071, Japan
Office: Bldg. Fujimi, 7F Room 710
E-mail:shinando[\at]ed[\dot]tus[\dot]ac[\dot]jp

----

住所:〒102-0071 千代田区富士見1-11-2 
居室:神楽坂キャンパス富士見校舎710号室
電話:03-3288-2501 (代)
Following Mathematica codes are provided courtesy of following contributors:Mr. Theerasak Thanomphongphan, Mr. Chan Ratha, and Shin Ando
* Cutting-Plane Linear SVM (coming soon)
* Area Under the ROC Curve (AUC)
* k-means++ [[[Arthur and Vassilvitsukji 2007]|http://portal.acm.org/citation.cfm?id=1283494]]
* Spectral Clustering [[[Shi and Malik 2000]|http://dx.doi.org/10.1109/34.868688]]
* Local Outlier Factor (LOF) [[[Breunig 2000]|http://portal.acm.org/citation.cfm?id=335388]]
* Breadth-First Score Ensemble [[[Lazarevic 2005]|http://dx.doi.org/10.1145/1081870.1081891]]
To access the codes, please read the [[Copyright and Disclaimers|https://sites.google.com/a/gunma-u.ac.jp/dm-codelets/home]] 
[[Welcome]] 
[[What's New]]
Ph. D. in Electronics Engineering (2004)
Department of Electronics Engineering, School of Engineering, University of Tokyo

M.E. in Information and Communication Engineering (2001)
Department of Information and Communication Engineering, School of Engineering, University of Tokyo

B.E. in Information and Communication Engineering (1999)
Department of Information and Communication Engineering, Faculty of Engineering, University of Tokyo 
----
博士(工学) 2004年 東京大学大学院工学系研究科電子工学専攻

修士(工学) 2001年 東京大学大学院工学系研究科電子情報工学専攻

学士(工学) 1999年 東京大学工学部電子情報工学科
[[Knowledge and Information Systems|https://jcr.incites.thomsonreuters.com/JCRMasterSearchAction.action?pg=SEARCH&searchString=information%20sciences#]]
[[Data Mining and Knowledge Discovery|https://jcr.incites.thomsonreuters.com/JCRMasterSearchAction.action?pg=SEARCH&searchString=information%20sciences#]]
[[Genetic and Evolvable Machines|jcr.incites.thomsonreuters.com/JCRMasterSearchAction.action?pg=SEARCH&searchString=information%20sciences#]]
[[Information Sciences|https://jcr.incites.thomsonreuters.com/JCRMasterSearchAction.action?pg=SEARCH&searchString=information%20sciences#]]
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''Call directly into TW core utility routines, define new functions, calculate values, add dynamically-generated TiddlyWiki-formatted output'' into tiddler content, or perform any other programmatic actions each time the tiddler is rendered.
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* [[TKDD|http://tkdd.cs.uiuc.edu/]], ACM - [[Submission|http://mc.manuscriptcentral.com/tkdd]] 
* [[JMLR|http://jmlr.csail.mit.edu/author-info.html]]
* [[TKDE|http://www.computer.org/portal/web/tkde/author]], IEEE 
* [[Machine Learning|http://www.editorialmanager.com/mach/default.asp]]
* [[KaIS|http://www.editorialmanager.com/kais/]]
* [[DMKD|http://www.editorialmanager.com/dami/]]
講義に関する情報は[[シラバス|https://class.admin.tus.ac.jp]] および [[LETUS|https://letus.ed.tus.ac.jp]] を参照してください

[[Syllabus|https://class.admin.tus.ac.jp]] 

*[[Thesis Topics|http://www.rs.tus.ac.jp/management/education/seminar/ando_lab/index.html]] (in Japanese) ([[ゼミナール・卒業研究紹介(大学HP)|http://www.rs.tus.ac.jp/management/education/seminar/ando_lab/index.html]])
*[[Demonstration Programs|http://www.rs.tus.ac.jp/ando/mathematica_demos.html]] ([[デモプログラム|http://www.rs.tus.ac.jp/ando/mathematica_demos.html]])
*[[Internship Study-abroad Seminar|http://www.rs.tus.ac.jp/ando/internship_study_abroad.html]] ([[インターンシップ・留学セミナー|http://www.rs.tus.ac.jp/ando/internship_study_abroad.html]])

!2019年度
!! オフィスアワー Office Hours 
*月曜 (Mon) 12:00-12:45 @F101
*金曜 (Fri) 12:00-12:45 @710
!!前期 First Semister
*データサイエンスの基礎2(金Fri 3)
*プログラミング論1 Programming 1 (月Mon 2)
*ゼミナール1 Seminar 1 (水 Wed 3)
*パターン認識 Pattern Recognition (金Fri 2)
*卒業研究1 Thesis Study 1 (水 Wed 2)
!!後期 Second Semister
*データサイエンスの基礎2(金Fri 3)
*プログラミング論1 Programming 1 (月Mon 2)
*ゼミナール2 Seminar 2 (水 Wed 3)
*パターン認識 Pattern Recognition (金Fri 2)
*卒業研究1 Thesis Study 2 (水 Wed 2)


!2016年度
!!前期
*データサイエンスの基礎I (金Fri 3)
*ゼミナールI Seminar 1A (水 Wed 2)
*ゼミナールII Seminar 2A (水 Wed 3)
*卒業研究 Thesis Study
*知識情報処理I Knowledge and Information Processing 1 (金 Fri 3)

!!後期
*データサイエンスの基礎II (金Fri 3)
*ゼミナールI Seminar 1B (水 Wed 2)
*ゼミナールII Seminar 2B (水 Wed 3)
*卒業研究 Thesis Study
*知識情報処理II Knowledge and Information Processing 2 (金 Fri 3)
*知識情報科学特論 Knowledge and Information Science (木 Thu 2/金 Fri 4)

!2015年度

!!前期
*情報処理概論 Introduction to Information Processing (火 Tue 3)
*ゼミナールI Seminar 1A (水 Wed 2)
*ゼミナールII Seminar 2A (水 Wed 3)
*卒業研究 Thesis Study
*システム分析 System Analysis (火 Tue 4)
*知識情報処理1 Knowledge and Information Processing 1 (木 Thu 2)
*知識情報科学1 Knowledge and Information Science 1 (火 Tue 2)

!!後期
*ゼミナールI Seminar 1B (水 Wed 2)
*ゼミナールII Seminar 2B (水 Wed 3)
*卒業研究 Thesis Study
*システム設計 System Design (火 Tue 4)
*知識情報処理2 Knowledge and Information Processing 1 (木 Thu 2)
*知識情報科学2 Knowledge and Information Science 1 (火 Tue 2)

!2014年度
!!前期
*キャリアデザイン Career Design 1
*情報処理概論 Introduction to Information Processing  
*ゼミナール Seminar 1A
*ゼミナール Seminar 2A
*システム分析 System Analysis
*知識情報処理 Knowlege and Information Processing 1
*知識情報科学 Knowledge and Information Science 1

!!後期
*ゼミナール Seminar 1B
*ゼミナール Seminar 2B
*システム設計 System Design
*知識情報処理 Knowledge and Information Processing 2
*知識情報科学 Knowledge and Information Science 2
*情報システム実習 Information Systems (Exercise)

! データ解析コンペティション
[[平成26年度データ解析コンペティション|http://jasmac-j.jimdo.com/データ解析コンペティション/平成26年度/]]に経営情報コースのチーム「坊っちゃんデータ解析部」(発表者:河合未夢)で参加しました
3/7に開催されたJIMS合同部会の成果報告会では最優秀賞を受賞し,全体での成果報告会に選抜されました
3/13に開催された全体での成果報告会では[[ビッグデータチャレンジ賞|http://bd.comp.ae.keio.ac.jp/2015/03/13/18/]]を受賞しました
[[Welcome/ようこそ|Welcome]]
[[Affiliation/所属|Affiliation]]
[[Education/学位|Education]]
[[Experience/職歴|Professional Experience]]
[[Contact/連絡先|Contact]]
[[Topics/研究テーマ|Topics]]
[[Selected Publications]]
[[主要論文(英文)|Selected Publications]]
[[主要論文(和文)]]
[[Bibliography Data|Bibliography]]
[[Supplementary Data]]
----
[[Research|research/research.html]] / [[研究内容|research/research.html]]
[[What's New]] / [[お知らせ|What's New]]
[[Lectures]] / [[講義情報|Lectures]] 
----
<script type="text/javascript">
var gaJsHost = (("https:" == document.location.protocol) ? "https://ssl." : "http://www.");
document.write(unescape("%3Cscript src='" + gaJsHost + "google-analytics.com/ga.js' type='text/javascript'%3E%3C/script%3E"));
</script>
<script type="text/javascript">
try {
var pageTracker = _gat._getTracker("UA-8513898-1");
pageTracker._trackPageview();
} catch(err) {}</script>
<html>
<script type="text/javascript" src="http://www.wolfram.com/cdf-player/plugin/v2.1/cdfplugin.js"></script>
<script type="text/javascript">
var cdf = new cdfplugin();
cdf.setDefaultContent('<a href="http://www.wolfram.com/cdf-player/"><img  src="単回帰Manipuate.png"></a>');
cdf.embed('単回帰Manipuate.cdf', 482, 787);
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</html>
!LEMIR 
*First International Workshop on LEarning and Mining for Robotics (in conjuction with ECML/PKDD 2009)
<html>
<img src=http://www.i.kyushu-u.ac.jp/~suzuki/head.png width=300 alt="poster.jpg">
</html>
*For more details, see the [[workshop website|http://www.i.kyushu-u.ac.jp/~suzuki/lemir.html]]
;2002-2003
Research Assistant for 21st Century COE 
Department of Electronics Engineering, School of Engineering, University of Tokyo

東京大学大学院工学系研究科電子工学専攻 21世紀COEリサーチアシスタント 

;2003-2004
Post Doctoral Researcher of Japanese Society for Promotion of Science 
Interdiciplanary Graduate School of Frontier Science,  University of Tokyo

東京大学大学院新領域創成研究科 学術振興会特別研究員

;2004-2005
Post Doctoral Researcher of Japanese Society for Promotion of Science 
Interdiciplanary Graduate School of Science and Engineering, Tokyo Institute of Techonology

東京工業大学大学院総合理工学研究科 学術振興会特別研究員

;2005-2008
Research Associate 
Faculty of Engineering, Yokohama National University

横浜国立大学工学研究院 助手(特別研究教員)

;2008-2013
Assistant Professor 
Faculty of Engineering, Gunma University

群馬大学大学院工学研究科 助教

;2014-2016
Senior Lecturer
School of Management, Tokyo University of Science

東京理科大学経営学部 講師

;2017-Present
Associate Professor
School of Management, Tokyo University of Science

東京理科大学経営学部 准教授
*Shin Ando and Einoshin Suzuki " Detecting Clusters of Outliers with Information Theoretic Clustering", Journal of Japanese Society of Artificial Intelligence, [[Vol.23, No. 5 pp.344-354, 2008|http://www.jstage.jst.go.jp/article/tjsai/18/5/18_305/_article/-char/ja/]]
*Shin Ando, Jun Sakuma, Einoshin Suzuki, Shigenobu Kobayashi, "An Information Theoretic Approach to Detection of Minority Subsets",  Journal of Japanese Society of Artificial Intelligence, Vol.22, No.3, 2007. 
* Shin Ando, Hitoshi Iba,"Evolutionary Optimization of Network Structure using Informative Genotype Tag", Journal of Japanese Society of Artificial Intelligence,Vol. 18, No.5, 2003 Full Text
* Shin Ando, Hitoshi Iba,"Evolution of Analog Circuits using Variable Length Chromosomes, Journal of Japanese Society of Artificial Intelligence, Vol.15, No.5, No.9A8, 2000
[[DOI:10.1137/1.9781611972832.51|http://doi.dx.org/10.1137/1.9781611972832.51]]

!Trajectory Dataset

!!Pivot Behavior Trajectory [[[1]|References]]
Format: Matlab
*Datasets are prepared for 3-fold cross-validation, processed from 3 trajectories of an agent.  
*Each fold consists of training/validation set of subsequences of velocity norm
*Each subsequence is a 18-dimensional vector.
*The zip files contain training/validation sets named in the format "cv?{trn/vld}.mat"
[[Data|http://anis.dept.eng.gunma-u.ac.jp/~dataset/data_tall.zip]] [[Label|http://anis.dept.eng.gunma-u.ac.jp/~dataset/label_tall.zip]]

!!Interactive Behavior Trajectory [[[2]|References]]
Format: Matlab (Zipped) 

Datasets """PX"""1-3 are processed respectively from an independent set of agent trajectories.
Each dataset has been prepared for a 5-fold cross-validation. 
Each fold consists of training/validation set of 3528/882 subsequences of velocity norm (real-value vectors).
Each zip files contain training/validation sets named in the format "cv?{trn/vld}.mat"
*"""PX"""1 [[Data|http://anis.dept.eng.gunma-u.ac.jp/~dataset/data_px1.zip]] [[Label|http://anis.dept.eng.gunma-u.ac.jp/~dataset/label_px1.zip]]
*"""PX"""2 [[Data|http://anis.dept.eng.gunma-u.ac.jp/~dataset/data_px2.zip]] [[Label|http://anis.dept.eng.gunma-u.ac.jp/~dataset/label_px2.zip]]
*"""PX"""3 [[Data|http://anis.dept.eng.gunma-u.ac.jp/~dataset/data_px3.zip]] [[Label|http://anis.dept.eng.gunma-u.ac.jp/~dataset/label_px3.zip]]

!!Sensor Tag Data [[[3]|References]]
Format: Mathematica Package/Matlab
*Datasets S1-4 are processed from trajectories of [[Localization Data for Person Activity Data Set|http://archive.ics.uci.edu/ml/datasets/Localization+Data+for+Person+Activity]] from [[UCI machine learning repository|http://archive.ics.uci.edu/ml/index.html]]
*The Mathematica Package below generates 3-fold cross-validation datasets
[[SensorTagDataCV.m|http://anis.dept.eng.gunma-u.ac.jp/~dataset/SensorTagDataCV.m]]

*Instructions
** Load the package by {{{<<SensorTagDataCV`}}} and execute {{{SensorTagDataCV[url]}}} in Mathematica
**url is the path to the mat file. It can also be a local path to a downloaded file
**current link is "http://archive.ics.uci.edu/ml/machine-learning-databases/00196/ConfLongDemo_JSI.txt"
* Files are generated to the current directory
**Each file contains a training/validation set and named in the format "data_st?cv?{trn/vld}.mat"

!!Handwriting Data [[[4]|References]]
Format: Mathematica Package/Matlab
*Datasets H1-3 are processed from trajectories of [[Character Trajectories Data Set|http://archive.ics.uci.edu/ml/datasets/Character+Trajectories]] from [[UCI machine learning repository|http://archive.ics.uci.edu/ml/index.html]]
* The Mathematica package below generates 3-fold cross-validation datasets
[[HandwritingDataCV.m|http://anis.dept.eng.gunma-u.ac.jp/~dataset/HandwritingDataCV.m]]
*Instructions
** Load the package by {{{<<HandwritingDataCV`}}} and execute {{{HandwritingDataCV[url]}}} in Mathematica
**url is the path to the mat file. It can also be a local path to a downloaded file
**current link is 'http://ftp.ics.uci.edu/pub/machine-learning-databases/character-trajectories/mixoutALL_shifted.mat'
* Files are generated to the current directory
**Each file contains a training/validation set and named in the format "data_hw?cv?{trn/vld}.mat"

!Synthetic Time Series
!!"""Cylinder-Bell-Funnel""" Function [[[5]|References]]
*Format: Mathematica Package/Matlab
*The Mathematica Package below generates a training/test split instance 
[[SyntheticTimeSeriesData.m|http://anis.dept.eng.gunma-u.ac.jp/~datasets/SyntheticTimeSeriesData.m]]
*Instruction
** Load the package by {{{<<SyntheticTimeSeriesData`}}} and execute {{{CBFData[]}}} in Mathematica
** Training/test data/labels are stored in the local directory in separate files.

!!Control Chart [[[6]|References]]
*Format: Mathematica Package/Matlab
*The Mathematica Package below formats a benchmark instance made public at [[UCR|http://www.cs.ucr.edu/~eamonn/time_series_data/]]
[[SyntheticTimeSeriesData.m|http://anis.dept.eng.gunma-u.ac.jp/~datasets/SyntheticTimeSeriesData.m]]
*Instruction
** Load the package by {{{<<SyntheticTimeSeriesData`}}} and execute {{{ControlChartData[]}}} in Mathematica
** Training/test data/labels are stored in the local directory in separate files.
*Shin Ando and , """"Discriminative Prototype Set Learning for Nearest Neighbor Learning"""," In Proceedings of 2018 SIAM International Conference on Data Mining pp.468-476 (DOI:[[10.1137/1.9781611975321.53|http://dx.doi.org/10.1137/1.9781611975321.53]]) [[PDF|http://epubs.siam.org/doi/pdf/10.1137/1.9781611975321.53]] 
*Shin Ando, """Chun-Yuan Huang"""; "Deep Over-sampling Framework for Classifying Imbalanced Data," in Machine Learning and Knowledge Discovery in Databases (LNCS 10534), Springer, 2017, 770-785  (DOI:[[10.1007/978-3-319-71249-9_46|https://doi.org/10.1007/978-3-319-71249-9_46]]) [[Preprint|https://arxiv.org/abs/1704.07515]]
*Shin Ando, "Classifying Imbalanced Data in Distance-based Feature Space," //Knowledge and Information Systems//, 46, 707-730 (2015),  (DOI:[[10.1007/s10115-015-0846-3|http://dx.doi.org/10.1007/s10115-015-0846-3]]) [[readcube|http://rdcu.be/mTvG]]
*Shin Ando and Einoshin Suzuki, "Minimizing Response Time in Time Series Classification," //Knowledge and Information Systems//, 42, 449-476 (2015),  (DOI:[[10.1007/s10115-015-0826-7|http://dx.doi.org/10.1007/s10115-015-0826-7]]) [[readcube|http://rdcu.be/mTv2]]
*Shin Ando, Theerasak Thanomphongphan, Youichi Seki, Einoshin Suzuki, "Ensemble Anomaly Detection from Multi-resolution Trajectory Features," //Data Mining and Knowledge Discovery//, Volume 29, Issue 1 (2015), Page 39-83 (DOI:[[10.1007/s10618-013-0334-x|http://dx.doi.org/10.1007/s10618-013-0334-x]]) [[readcube|http://rdcu.be/mTwg]]
*Shin Ando and Einoshin Suzuki, "Discriminative Learning on Exemplary Patterns in Sequential Numerical Data," In Proceedings of the 2014 IEEE International Conference on Data Mining (ICDM), pp.1-10, 2014 [[DOI|http://dx.doi.org/10.1109/ICDM.2014.122|]] ([[Supplementary Data]])
*Shin Ando and Einoshin Suzuki, """"Time-Sensitive""" Classification of Behavioral Data," In Proceedings of 2013 SIAM International Conference on Data Mining pp.458-466 (DOI:[[10.1137/1.9781611972832.51|http://dx.doi.org/10.1137/1.9781611972832.51]]) [[PDF|http://epubs.siam.org/doi/pdf/10.1137/1.9781611972832.51]] [[Supplementary Data]]
*Shin Ando, """Performance-Optimizing""" Classification of Time-series based on Nearest Neighbor Density Approximation, In """SSTDM-12""", IEEE 12th International Conference on Data Mining Workshops (ICDMW), 2012  (DOI:[[10.1109/ICDMW.2012.14|http://dx.doi.org/10.1109/ICDMW.2012.14]]). 
*Shin Ando and Einoshin Suzuki,"Role-behavior Analysis from Trajectory Data by Cross-domain Learning", in Procs. of Data Mining (ICDM), 2011 IEEE 11th International Conference on, pp.21-30, 2011 (DOI:[[10.1109/ICDM.2011.125|http://dx.doi.org/10.1109/ICDM.2011.125]])
*Shin Ando, "Latent Feature Encoding using Dyadic and Relational Data", in Proceedings of the 20th ACM International Conference on Information and Knowledge Management, pp.2201-2204, 2011 (DOI:[[10.1145/2063576.2063926|http://dx.doi.org/10.1145/2063576.2063926]])
* Shin Ando, Theerasak Tanomphongphan,  Daisuke Hoshino, Youichi Seki, and Einoshin Suzuki; "ACE: Anomaly Clustering Ensemble for Multi-perspective Anomaly Detection in Robot Behaviors," in Proceedings of 2011 SIAM International Conference on Data Mining ([[DOI:10.1137/1.9781611972818.1|http://dx.doi.org/10.1137/1.9781611972818.1]]), pp.55-68, 2011.  [[PDF|http://siam.omnibooksonline.com/data/papers/055.pdf#page=1]] [[Supplementary data|http://www.i.kyushu-u.ac.jp/~suzuki/SDM11data.zip]] (Property of [[JST-ANR project|http://www.i.kyushu-u.ac.jp/~suzuki/jstanr.htm]]) 
* Shin Ando and Einoshin Suzuki, "Detection of Unique Temporal Segments by Information Theoretic Meta-clustering" in Proceedings of the 15th ACM SIGKDD Conference on Knowledge Discovery and Data Mining ("""KDD-09"""), pp.59-68, 2009. (DOI:[[10.1145/1557019.1557033|http://doi.acm.org/10.1145/1557019.1557033]]) [[PowerPoint/Video|http://videolectures.net/kdd09_ando_dutsitmc/]]  [[Supplementary Data]]
* Shin Ando and Einoshin Suzuki, "Unsupervised Cross-domain Learning by Interaction Information Co-clustering," in Proceedings of 8th IEEE International Conference on Data Mining (~ICDM08), pp. 13-22, 2008. [[Abstract|http://doi.ieeecomputersociety.org/10.1109/ICDM.2008.92]]
*Shin Ando "Clustering Needles in a Haystack: An Information Theoretic Analysis of Minority and Outlier Detection," in Proceedings of 7th IEEE International Conference on Data Mining (ICDM'07), pp. 13-22, 2007. [[Abstract|http://doi.ieeecomputersociety.org/10.1109/ICDM.2007.53]]
* Shin Ando "Heuristic Speciation for Evolving Neural Network Ensembles", in Proceedings of 2007 Genetic and Evolutionary Computation ~COnference (GECCO 2007), pp. 1766-1773, ACM Press, 2007. [[Abstract|http://doi.acm.org/10.1145/1276958.1277315]]
* Shin Ando and Einoshin Suzuki, "An Information Theoretic Approach to Detection of Minority Subsets in Database", in Proceedings of the 6th International Conference on Data Mining (ICDM'06), pp. 11-20, 2006. [[Abstract|http://doi.ieeecomputersociety.org/10.1109/ICDM.2006.19]]
* Shin Ando, Jun Sakuma, and Shigenobu Kobayashi, "Adaptive isolation model using data clustering for multimodal function optimization" in Proceedings of the 2005 Genetic and Evolutionary Computation ~COnference (~GECCO2005), pp. 1417-1424, 2005. [[Abstract|http://doi.acm.org/10.1145/1068009.1068235]]
* Shin Ando, Hitoshi Iba,"Classification of Gene Expression Profile Using Combinatory Method of Evolutionary Computation and Machine Learning", ed.Wolfgang Banzhaf, Vol. 5, pp. 145-156, Genetic Programming and Evolvable Machines, Kluwer Publishing, 2004 [[Abstract|http://dx.doi.org/10.1023/B:GENP.0000023685.83861.69]]
* Shin Ando, Hitoshi Iba,"Variable Length Chromosomes for Analog Evolvable Hardware",eds. A Ghosh and S Tsutsui, Advances in Evolutionary Computation, pp. 643-662, ~Springer-Verlag, 2003 [[Abstract|http://dx.doi.org/10.1007/978-3-642-18965-4_25]]
* Shin Ando, Hitoshi Iba,"Construction of Genetic Network using Evolutionary Algorithm and Combined Fitness Function" Genome Informatics, 14: 94-103, 2002  [[Abstract|http://www.ncbi.nlm.nih.gov/pubmed/15706524]] [[PDF|http://www.ncbi.nlm.nih.gov/pubmed/15706524]] 
* Shin Ando, Hitoshi Iba,"Evolutionary Modeling and Inference by Genetic Network" Information Science, Vol. 145, Iss. 3-4, Elsevier Science 2001 [[Abstract|http://dx.doi.org/10.1016/S0020-0255(02)00235-9]] 
Associate Professor [[School of Management, Tokyo University of Science|http://www.rs.tus.ac.jp/management]]
[[Shin Ando|http://www.rs.tus.ac.jp/ando/]]
![[ICDM14|http://icdm2014.sfu.ca/program_accepted_papers.html]]
Following are Mathematica packages for generating the datasets used in the experiments.
To generate the datasets, load the package in Mathematica, then run
{{{CrossValidationDatasets[]}}}
Matlab files will be generated in the working directory. each matlab file contains a dataset-labels pair.

*;V.A.1 Silhouette Data [[(Mathematica Package)|SilhouetteData.m]]

*;V.A.2 Joint Recognition Data [[(Mathematica Package)|JointRecognitionData.m]]

*;V.A.3 Multiagent Interaction Data [[(Mathematica Package)|MultiagentInteractionData.m]]

*;V.A.4 Person Activity Data [[(Mathematica Package)|PersonActivityData.m]]

*;V.A.5 Physical Action Data [[(Mathematica Package)|PhysicalActionData.m]]


![[SDM13]]
[[Open instructions and links|SDM13]]

! [[ [KDD09]|http://doi.acm.org/10.1145/1557019.1557033]]
!!Dataset for the 1st Experiment (6.1.1 p.62)
*polydat_seq_i.txt
**1st Row	:<html><math display='block'>
   <semantics>
      <mrow>
         <mrow><mo>(</mo>
            <mrow>
               <msub>
                  <mi>t</mi>
                  <mn>1</mn>
               </msub>
               <mo>,</mo><mo>&hellip;</mo><mo>,</mo><msub>
                  <mi>t</mi>
                  <mrow>
                     <mn>12</mn>
                  </mrow>
               </msub>
               
            </mrow>
         <mo>)</mo></mrow>
         
      </mrow>
      <annotation encoding='MathType-MTEF'>
         
      </annotation>
   </semantics>
</math>
</html> (timestamp)
**2nd Row	: <html><math display='block'>
   <semantics>
      <msub>
         <mi>y</mi>
         <mn>1</mn>
      </msub>
      <mo>=</mo><mrow><mo>[</mo> <mrow>
         <msub>
            <mi>x</mi>
            <mn>1</mn>
         </msub>
         <mrow><mo>(</mo>
            <mrow>
               <msub>
                  <mi>t</mi>
                  <mn>1</mn>
               </msub>
               
            </mrow>
         <mo>)</mo></mrow>
         <mo>,</mo><mn>...</mn><mo>,</mo><msub>
            <mi>x</mi>
            <mn>1</mn>
         </msub>
         <mrow><mo>(</mo>
            <mrow>
               <msub>
                  <mi>t</mi>
                  <mrow>
                     <mn>12</mn>
                  </mrow>
               </msub>
               
            </mrow>
         <mo>)</mo></mrow>
         
      </mrow> <mo>]</mo></mrow>
      <annotation encoding='MathType-MTEF'>
         
      </annotation>
   </semantics>
</math>
</html> (sequencial observed value)
**3rd Row	: <html><math display='block'>
   <semantics>
      <msub>
         <mi>y</mi>
         <mn>2</mn>
      </msub>
      
      <annotation encoding='MathType-MTEF'>
         
      </annotation>
   </semantics>
</math>
</html>
**...
*polydat_lbl_i.txt
**1st Row:<html><math display='block'>
 <semantics>
  <msub>
   <mi>z</mi>
   <mn>1</mn>
  </msub>
  <mo>&#x2208;</mo><mrow><mo>{</mo> <mrow>
   <mn>0</mn><mo>,</mo><mn>1</mn>
  </mrow> <mo>}</mo></mrow>
 <annotation encoding='MathType-MTEF'>
 </annotation>
 </semantics>
</math>
</html> (class label )
**...
*[[zipped tar|polydat.tar.bz2]]
*note that these datasets are randomly generated as described in the publication but are seeded differently 
!!Artificial Intelligence/人工知能
*Deep learning models for temporal sequential data
----
*時系列データのためのディープラーニングモデル

!!Data Mining / データマイニング 
* Information Theoretic clustering 
* Mining minority objects in large datasets
----
*情報理論的クラスタリング
*異常値の検出

!!Soft Computing / ソフトコンピューティング
* Design and optimization techniques using Genetic Algorithm and several other Bio-inspired Computation methods
----
* 遺伝的アルゴリズムおよび進化計算に基づく設計・最適化手法

!!Applications / 応用
*Designing of electric circuits and neural networks
*Estimation of gene regulatory models
*Text and image classification.  
----
*電気回路・神経回路の設計
*遺伝子発現時系列のモデル推定
*テキスト・画像の分類
[img[pic.jpg|pic.jpg]]

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ここは[[安藤晋@東京理科大経営学部|https://www.google.co.jp/maps/place/%E5%AE%89%E8%97%A4%E7%A0%94%E7%A9%B6%E5%AE%A4+%E7%B5%8C%E5%96%B6%E5%AD%A6%E9%83%A8+%E6%9D%B1%E4%BA%AC%E7%90%86%E7%A7%91%E5%A4%A7%E5%AD%A6/@35.6964916,139.7437744,17z/data=!3m1!4b1!4m5!3m4!1s0x60188c4274c00001:0x921e8f7e23b3c394!8m2!3d35.6964916!4d139.7459631]]のホームページです.
左側のメニューから私のプロフィールをご覧になれます.
----
[[About my research|research/research.html]] / [[研究内容についてはこちらへ|research/research.html]]

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Oral presentation at ICAART 

"Visually-private Scene Classification with Agent-collected Weak-labels"

http://www.icaart.org/Abstracts/2021/AbstractICAART_2021_Abstracts.htm

Poster presentation at ICPRAM

"Adversarial Minority-class Re-sampling for Imbalanced Sequence Classification"

http://www.icpram.org/Abstracts/2021/AbstractICPRAM_2021_Abstracts.htm

----
令和2年度データ解析コンペティションDB部会最終報告会で優秀賞をいただきました


令和元年度データ解析コンペティションDB部会最終報告会で優秀賞をいただきました
https://www.tus.ac.jp/today/archive/20200313001.html
|Name|Co-located|Submission|Dates|
|[[IBIS|http://ibisml.org/ibis2011/]]|IBISML|9/16|11/7-9|
|[[LEMIR|http://www.i.kyushu-u.ac.jp/~suzuki/lemir2011.html]]|ICDM|8/4|12/10|
*須賀佑太朗,関庸一,安藤晋 「特徴的部分系列に基づく時系列及び形状系列の判別分析 情報処理学会論文誌数理モデル化と応用(TOM), 2015 [[情報学広場|http://id.nii.ac.jp/1001/00144449]]
*多賀谷 侑史,安藤 晋,関 庸一 「サンプルの所属度に応じた可変自己組織化マップ 情報処理学会論文誌数理モデル化と応用(TOM), 2012, 5, 1-13 [[情報学広場|http://id.nii.ac.jp/1001/00085812/]]
*中村 友哉,清水 美和,藍原 雅一,安藤 晋,関 庸一 「世帯特性と素材特性を考慮した階層的メニューレコメンデーションシステム」 オペレーションズ・リサーチ(特集:データ解析コンペティション:食卓データの分析), 2010, 55, 91-97 [[CiNii|http://ci.nii.ac.jp/naid/110007539541]]
*安藤 晋,鈴木 英之進. 「情報理論的クラスタリングによる異常値クラスタの検出」,人工知能学会論文誌,Vol. 23 (2008) No. 5,pp.344-354 [[JSTAGE|http://www.jstage.jst.go.jp/article/tjsai/23/5/23_344/_article/-char/ja/]] [[修正版|jsai08_revised.pdf]]
*佐久間 淳,安藤 晋,小林 重信.「 混合分布推定のためのコンポーネントワイズEM」,人工知能学会論文誌,Vol. 23 (2008) ,No. 3, pp.163-175 [[JSTAGE|http://www.jstage.jst.go.jp/article/tjsai/23/3/23_163/_article/-char/ja/]]
*安藤 晋,佐久間 淳,鈴木 英之進,小林 重信. 「情報理論的枠組に基づくマイノリティ集合の検出」,人工知能学会論文誌,Vol. 22 (2007),No. 3,pp.311-321 [[JSTAGE|http://www.jstage.jst.go.jp/article/tjsai/22/3/22_311/_article/-char/ja/]]
* 安藤 晋,伊庭 斉志. 「タグ付遺伝子型を用いたネットワーク構造の進化的学習と最適化」,  人工知能学会論文誌,Vol. 18 (2003) No. 5,pp.305-315 [[JSTAGE|http://www.jstage.jst.go.jp/article/tjsai/18/5/18_305/_article/-char/ja/]]