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, University of HelsinkiVerified email at helsinki.fi
Ville HyvönenPostdoctoral researcher, Aalto University, Department of Computer ScienceVerified email at aalto.fi
Antti OulasvirtaProfessor, Aalto UniversityVerified email at aalto.fi
Jukka CoranderUiO, Wellcome Sanger Institute, University of HelsinkiVerified email at medisin.uio.no
Liang WangUniversity of HelsinkiVerified email at cl.cam.ac.uk
Jussi MäättäVerified email at helsinki.fi
Ivo GrosseProfessor of Bioinformatics, Martin Luther University Halle-WittenbergVerified email at informatik.uni-halle.de
Ralf EggelingUniversity 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
Shridatt SugrimRutgers UniversityVerified email at winlab.rutgers.edu
Michael ShermanUniversity of ChicagoVerified email at uchicago.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

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	1347	2002
A statistical modeling approach to location estimation T Roos, P Myllymaki, H Tirri IEEE Transactions on Mobile Computing 1 (1), 59-69, 2002	480	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	370	2007
On discriminative Bayesian network classifiers and logistic regression T Roos, H Wettig, P Grünwald, P Myllymäki, H Tirri Machine Learning 59, 267-296, 2005	167	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	148	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	121	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	110	2007
Semi-supervised learning for WLAN positioning T Pulkkinen, T Roos, P Myllymäki 21st International Conference on Artificial Neural Networks (ICANN-2011 …, 2011	93	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	93	2009
Minimum description length revisited P Grünwald, T Roos International Journal of Mathematics for Industry, 2020	92	2020
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	77	2008
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	73*	2016
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	72	2011
On sequentially normalized maximum likelihood models T Roos, J Rissanen 1st Workshop on Information Theoretic Methods in Science and Engineering …, 2008	67	2008
MDL denoising revisited T Roos, P Myllymaki, J Rissanen IEEE Transactions on Signal Processing 57 (9), 3347-3360, 2009	64	2009
Transfer learning with ensembles of deep neural networks for skin cancer detection in imbalanced data sets AS Qureshi, T Roos Neural Processing Letters 55, 4461–4479, 2023	56	2023
AI-generated content: Authorship and inventorship in the age of artificial intelligence RM Ballardini, K He, T Roos Online Distribution of Content in the EU, 2019	53	2019
Conditional NML universal models J Rissanen, T Roos 2007 Information Theory and Applications Workshop, 337-341, 2007	53	2007
Learning locally minimax optimal Bayesian networks T Silander, T Roos, P Myllymäki International Journal of Approximate Reasoning 51 (5), 544-557, 2010	52	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	52	2008

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