Teemu Roos

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Petri MyllymakiProfessor of Computer Science, University of HelsinkiVerified email at helsinki.fi
Tomi SilanderResearcherVerified email at naverlabs.com
Peter GrünwaldGroup Leader Machine Learning, CWI; Professor of Statistics, Leiden UniversityVerified email at cwi.nl
Sotiris TasoulisDepartment of Computer Science and Biomedical Informatics, University of Thessaly.Verified email at uth.gr
Elias JääsaariPhD Student, Carnegie Mellon UniversityVerified email at andrew.cmu.edu
Antti OulasvirtaAalto UniversityVerified email at aalto.fi
Liang WangUniversity of CambridgeVerified email at cl.cam.ac.uk
Ville HyvönenPhD Student, University of Helsinki, Department of Computer ScienceVerified email at helsinki.fi
Ivo GrosseProfessor of Bioinformatics, Martin Luther University Halle-WittenbergVerified email at informatik.uni-halle.de
Ralf EggelingPostdoctoral researcher, University of TübingenVerified email at informatik.uni-tuebingen.de
Kazuho WatanabeToyohashi University of TechnologyVerified email at cs.tut.ac.jp
Yulong YangRutgers UniversityVerified email at scarletmail.rutgers.edu
Janne LindqvistAalto University (Computer Science)Verified email at aalto.fi
Michael ShermanEngineering Researcher at WINLAB, Rutgers UniversityVerified email at winlab.rutgers.edu
Shridatt SugrimRutgers UniversityVerified email at winlab.rutgers.edu
Jussi KangasharjuProfessor of Computer Science, University of HelsinkiVerified email at helsinki.fi
Teemu PulkkinenResearch Scientist, EkahauVerified email at ekahau.com
Alexandra M CarvalhoAssistant Professor, Instituto Superior Técnico, Technical University of LisbonVerified email at tecnico.ulisboa.pt
Arlindo L OliveiraDistinguished Professor, Instituto Superior Técnico / INESC-IDVerified email at tecnico.ulisboa.pt
Johan PensarAssociate Professor, Statistics and Data Science, University of OsloVerified email at math.uio.no

Teemu Roos

Professor at University of Helsinki

Verified email at helsinki.fi - Homepage

Machine Learning #UnivHelsinkiCS


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A probabilistic approach to WLAN user location estimation T Roos, P Myllymäki, H Tirri, P Misikangas, J Sievänen International Journal of Wireless Information Networks 9, 155-164, 2002	1321	2002
A statistical modeling approach to location estimation T Roos, P Myllymaki, H Tirri IEEE Transactions on Mobile Computing 1 (1), 59-69, 2002	466	2002
Location estimation in wireless telecommunication networks P Myllymäki, H Tirri, P Kontkanen, J Lahtinen, T Silander, T Roos, ... US Patent 7,228,136, 2007	358	2007
On discriminative Bayesian network classifiers and logistic regression T Roos, H Wettig, P Grünwald, P Myllymäki, H Tirri Machine Learning 59 (3), 267, 2005	152	2005
User-generated free-form gestures for authentication: Security and memorability M Sherman, G Clark, Y Yang, S Sugrim, A Modig, J Lindqvist, A Oulasvirta, ... 12th Annual International Conference on Mobile Systems, Applications, and …, 2014	134	2014
Topics in probabilistic location estimation in wireless networks P Kontkanen, P Myllymaki, T Roos, H Tirri, K Valtonen, H Wettig 2004 IEEE 15th International Symposium on Personal, Indoor and Mobile Radio …, 2004	119	2004
Error estimate concerning a target device's location operable to move in a wireless environment P Myllymäki, P Kontkanen, T Roos, K Valtonen, J Lahtinen, H Wettig, ... US Patent 7,209,752, 2007	105	2007
Semi-supervised learning for WLAN positioning T Pulkkinen, T Roos, P Myllymäki 21st International Conference on Artificial Neural Networks (ICANN-2011 …, 2011	87	2011
Evaluating methods for computer-assisted stemmatology using artificial benchmark data sets T Roos, T Heikkilä Literary and Linguistic Computing 24 (4), 417-433, 2009	81	2009
Discriminative learning of Bayesian networks via factorized conditional log-likelihood AM Carvalho, T Roos, AL Oliveira, P Myllymäki Journal of Machine Learning Research 12 (Jul), 2181-2210, 2011	67	2011
Factorized normalized maximum likelihood criterion for learning Bayesian network structures T Silander, T Roos, P Kontkanen, P Myllymäki 4th European Workshop on Probabilistic Graphical Models (PGM-08), 257-272, 2008	67	2008
On sequentially normalized maximum likelihood models T Roos, J Rissanen 1st Workshop on Information Theoretic Methods in Science and Engineering …, 2008	61	2008
Minimum description length revisited P Grünwald, T Roos International Journal of Mathematics for Industry, 2020	58	2020
MDL denoising revisited T Roos, P Myllymaki, J Rissanen IEEE Transactions on Signal Processing 57 (9), 3347-3360, 2009	56	2009
Fast nearest neighbor search through sparse random projections and voting V Hyvönen, T Pitkänen, S Tasoulis, E Jääsaari, R Tuomainen, L Wang, ... 2016 IEEE International Conference on Big Data, 881-888, 2016	50	2016
Conditional NML universal models J Rissanen, T Roos 2007 Information Theory and Applications Workshop, 337-341, 2007	49	2007
Learning locally minimax optimal Bayesian networks T Silander, T Roos, P Myllymäki International Journal of Approximate Reasoning 51 (5), 544-557, 2010	48	2010
Bayesian network structure learning using factorized NML universal models T Roos, T Silander, P Kontkanen, P Myllymaki 2008 Information Theory and Applications Workshop, 272-276, 2008	42	2008
Inferring intra-motif dependencies of DNA binding sites from ChIP-seq data R Eggeling, T Roos, P Myllymäki, I Grosse BMC Bioinformatics 16 (1), 1-15, 2015	41	2015
An application of storage-optimal MatDot codes for coded matrix multiplication: Fast k-nearest neighbors estimation U Sheth, S Dutta, M Chaudhari, H Jeong, Y Yang, J Kohonen, T Roos, ... 2018 IEEE International Conference on Big Data, 1113-1120, 2018	40	2018

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