| Session-based Recommendations with Recurrent Neural Networks B Hidasi, A Karatzoglou, L Baltrunas, D Tikk arXiv preprint arXiv:1511.06939, 2015 | 3868 | 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 | 719 | 2009 |
| 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 | 612 | 2016 |
| Major components of the Gravity recommendation system G Takács, I Pilászy, B Németh, D Tikk ACM SIGKDD Explorations Newsletter 9 (2), 80-83, 2007 | 319 | 2007 |
| Alternating least squares for personalized ranking G Takács, D Tikk Proceedings of the sixth ACM conference on Recommender systems, 83-90, 2012 | 271 | 2012 |
| 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 | 262 | 2008 |
| Investigation of various matrix factorization methods for large recommender systems G Takács, I Pilászy, B Németh, D Tikk Proceedings of the 2nd KDD Workshop on Large-Scale Recommender Systems and …, 2008 | 240 | 2008 |
| 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 | 239 | 2010 |
| A comprehensive benchmark of kernel methods to extract protein–protein interactions from literature D Tikk, P Thomas, P Palaga, J Hakenberg, U Leser PLoS computational biology 6 (7), e1000837, 2010 | 225 | 2010 |
| Comprehensive analysis of a new fuzzy rule interpolation method D Tikk, P Baranyi IEEE Transactions on Fuzzy Systems 8 (3), 281-296, 2000 | 220 | 2000 |
| 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 | 205 | 2009 |
| 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 | 200 | 2003 |
| 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 | 198 | 2012 |
| 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 | 170 | 2005 |
| 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 | 158 | 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 | 134 | 2002 |
| General factorization framework for context-aware recommendations B Hidasi, D Tikk Data Mining and Knowledge Discovery, 1-30, 2015 | 128 | 2015 |
| Fuzzy rendszerek LT Kóczy, D Tikk Typotex, 2000 | 127* | 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 | 123 | 2007 |
| 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 | 119 | 2006 |
Balázs HidasiGravity R&D確認したメール アドレス: gravityrd.com