Domonkos Tikk

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Co-authors

Peter BaranyiSzechenyi Istvan University & Budapest University of TechnologyVerified email at sze.hu
Balázs HidasiGravity R&DVerified email at gravityrd.com
Alexandros KaratzoglouGoogleVerified email at google.com
Kevin Kok Wai WongMurdoch University, Perth, Western AustraliaVerified email at murdoch.edu.au
Gábor Takácsassociate professor, Széchenyi István University, Győr, HungaryVerified email at sze.hu
Illés SoltVerified email at gravityrd.com
Ulf LeserKnowledge Management in Bioinformatics, Humboldt-Universität zu BerlinVerified email at informatik.hu-berlin.de
Ron PattonProfessor of Control and Intelligent Systems Engineering, Hull UniversityVerified email at hull.ac.uk
Alan SaidUniversity of GothenburgVerified email at acm.org
Philippe ThomasGerman Research Center for Artificial IntelligenceVerified email at dfki.de
Paolo CremonesiDept. Computer Engineering, Politecnico di MilanoVerified email at polimi.it
Dávid ZibriczkyDB SchenkerVerified email at finance.bme.hu
Linas BaltrunasNetflixVerified email at netflix.com
Szilveszter KovacsAssociate Professor, University of MiskolcVerified email at iit.uni-miskolc.hu
Martha LarsonRadboud University and Delft University of TechnologyVerified email at tudelft.nl
Jörg HakenbergIllumina, Inc.Verified email at illumina.com
Magyar GáborBudapest University of Technology and EconomicsVerified email at tmit.bme.hu
József K. TarFull Professor, Óbuda University, Bejczy Antal iRobottechnikai KözpontVerified email at nik.uni-obuda.hu
Zsolt Csaba JohanyákJohn von Neumann University, Department of Information TechnologyVerified email at gamf.uni-neumann.hu
Massimo QuadranaPandora MediaVerified email at pandora.com

Domonkos Tikk

Gravity R&D

Verified email at gravityrd.com

machine learning text mining recommender systems


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Session-based recommendations with recurrent neural networks B Hidasi, A Karatzoglou, L Baltrunas, D Tikk arXiv preprint arXiv:1511.06939, 2015	936	2015
Scalable collaborative filtering approaches for large recommender systems G Takács, I Pilászy, B Németh, D Tikk The Journal of Machine Learning Research 10, 623-656, 2009	561	2009
Major components of the Gravity recommendation system G Takács, I Pilászy, B Németh, D Tikk ACM SIGKDD Explorations Newsletter 9 (2), 80-83, 2007	263	2007
Parallel recurrent neural network architectures for feature-rich session-based recommendations B Hidasi, M Quadrana, A Karatzoglou, D Tikk Proceedings of the 10th ACM Conference on Recommender Systems, 241-248, 2016	232	2016
Comprehensive analysis of a new fuzzy rule interpolation method D Tikk, P Baranyi IEEE Transactions on Fuzzy Systems 8 (3), 281-296, 2000	199	2000
A comprehensive benchmark of kernel methods to extract protein–protein interactions from literature D Tikk, P Thomas, P Palaga, J Hakenberg, U Leser PLoS Comput Biol 6 (7), e1000837, 2010	197	2010
Fast ALS-based matrix factorization for explicit and implicit feedback datasets I Pilászy, D Zibriczky, D Tikk Proceedings of the fourth ACM conference on Recommender systems, 71-78, 2010	190	2010
From differential equations to PDC controller design via numerical transformation P Baranyi, D Tikk, Y Yam, RJ Patton Computers in Industry 51 (3), 281-297, 2003	190	2003
Matrix factorization and neighbor based algorithms for the Netflix prize problem G Takács, I Pilászy, B Németh, D Tikk Proceedings of the 2008 ACM conference on Recommender systems, 267-274, 2008	189	2008
Investigation of various matrix factorization methods for large recommender systems G Takács, I Pilászy, B Németh, D Tikk 2008 IEEE International Conference on Data Mining Workshops, 553-562, 2008	187	2008
Recommending new movies: even a few ratings are more valuable than metadata I Pilászy, D Tikk Proceedings of the third ACM conference on Recommender systems, 93-100, 2009	180	2009
Fuzzy rule interpolation for multidimensional input spaces with applications: A case study KW Wong, D Tikk, TD Gedeon, LT Kóczy IEEE transactions on fuzzy systems 13 (6), 809-819, 2005	154	2005
Alternating least squares for personalized ranking G Takács, D Tikk Proceedings of the sixth ACM conference on Recommender systems, 83-90, 2012	151	2012
Fast ALS based tensor factorization for context-aware recommendation from implicit feedback B Hidasi, D Tikk Proceedings of the 2012 European conference on Machine Learning and …, 2012	138	2012
A survey on universal approximation and its limits in soft computing techniques D Tikk, LT Kóczy, TD Gedeon International Journal of Approximate Reasoning 33 (2), 185-202, 2003	134	2003
Stability of interpolative fuzzy KH controllers D Tikk, I Joó, L Kóczy, P Várlaki, B Moser, TD Gedeon Fuzzy Sets and Systems 125 (1), 105-119, 2002	112	2002
Fuzzy rule interpolation Matlab toolbox-FRI toolbox ZC Johanyák, D Tikk, S Kovács, KW Wong 2006 IEEE International Conference on Fuzzy Systems, 351-357, 2006	103	2006
Fuzzy rendszerek LT Kóczy, D Tikk Typotex, 2000	100*	2000
KDD cup and workshop 2007 J Bennett, C Elkan, B Liu, P Smyth, D Tikk ACM SIGKDD Explorations Newsletter 9 (2), 51-52, 2007	79	2007
Relation extraction for drug-drug interactions using ensemble learning P Thomas, M Neves, I Solt, D Tikk, U Leser Training 4 (2,402), 21,425-23,827, 2011	75	2011

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