Monday, August 17th; TIETOTALO building - Room TB109 8:45 – 9:30 Registration 9:30 – 10:30 Plenary Talk: Shun-ichi Amari (RIKEN Brain Science Institute,

Source URL: sp.cs.tut.fi

• University of Tampere
• Tampere
• Minimum description length
• Helsinki Institute for Information Technology
• Jorma Ollila
• University of Helsinki
• Helsinki
• Education in Finland
• Finland
• Jorma Rissanen

Call For Papers Workshop on Information Theoretic Methods in Science and Engineering Tampere, Finland August 18 – 20, 2008 Organizing

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• Jorma Rissanen
• Tampere
• Finland

Microsoft Word - WITMSE2010_-_CFP.rtf

Source URL: sp.cs.tut.fi

• Tampere
• Jorma Rissanen
• Finland

ON SEQUENTIALLY NORMALIZED MAXIMUM LIKELIHOOD MODELS Teemu Roos and Jorma Rissanen Helsinki Institute for Information Technology HIIT P.O.Box 68 (Department of Computer Science) FIUniversity of Helsinki, FINLAND t

Source URL: sp.cs.tut.fi

Preface The Sixth Workshop on Information Theoretic Methods in Science and Engineering (WITMSEwas held in Tokyo, Japan on August 26-29, 2013. This workshop is originally intended to promote interdisciplinary resea

Source URL: www.me.inf.kyushu-u.ac.jp

• Information theory
• Nicolò Cesa-Bianchi
• Keynote
• Science
• Academia
• Humanities
• University of Helsinki
• Jorma Rissanen
• Helsinki Institute for Information Technology

Call For Papers Workshop on Information Theoretic Methods in Science and Engineering Tampere, Finland August 17 – 19, 2009 Organizing

Source URL: sp.cs.tut.fi

• Tampere
• Paul Vitanyi
• Academic conference
• Knowledge
• Education
• Computing
• Tampere University of Technology
• University of Tampere
• Jorma Rissanen

Microsoft Word - IEEE_GENSIPS07_Program_06062007.doc

Source URL: www.cs.tut.fi

• Stuart Kauffman
• Jorma Rissanen
• Boolean network
• Academia
• Knowledge
• Science
• Tampere
• Genomics

AN MDL FRAMEWORK FOR DATA CLUSTERING Petri Kontkanen, Petri Myllym¨aki, Wray Buntine, Jorma Rissanen and Henry Tirri October 15, 2003

Source URL: cosco.hiit.fi

• Multivariate statistics
• Data mining
• Geostatistics
• Minimum description length
• Mixture model
• Consensus clustering
• Determining the number of clusters in a data set
• Statistics
• Cluster analysis
• Machine learning