| Session-based Recommendations with Recurrent Neural Networks B Hidasi, A Karatzoglou, L Baltrunas, D Tikk International Conference on Learning Representations ICLR 2016, 2016 | 2344 | 2016 |
| kernlab - An S4 Package for Kernel Methods in R A Karatzoglou, A Smola, K Hornik, A Zeileis Journal of Statistical Software 11 (9), 1-20, 2004 | 2089 | 2004 |
| Multiverse Recommendation: N-dimensional Tensor Factorization for Context-aware Collaborative Filtering A Karatzoglou, X Amatriain, L Baltrunas, N Oliver Proceedings of the fourth ACM Conference on Recommender Systems RecSys, 79-86, 2010 | 1014 | 2010 |
| Support Vector Machines in R A Karatzoglou, D Meyer, K Hornik Journal of Statistical Software 15 (09), 2006 | 796* | 2006 |
| Overcoming Catastrophic Forgetting with Hard Attention to the Task J Serrŕ, D Surís, M Miron, A Karatzoglou Proceedings of the 35th International Conference on Machine Learning ICML, 2018 | 690 | 2018 |
| Recurrent Neural Networks with Top-k Gains for Session-based Recommendations B Hidasi, A Karatzoglou Proceedings of the 27th ACM CIKM International Conference on Information and …, 2018 | 646 | 2018 |
| Personalizing Session-based Recommendations with Hierarchical Recurrent Neural Networks M Quadrana, A Karatzoglou, B Hidasi, P Cremonesi Proceedings of the Eleventh ACM Conference on Recommender Systems RecSys …, 2017 | 567 | 2017 |
| CoFiRank-Maximum Margin Matrix Factorization for Collaborative Ranking M Weimer, A Karatzoglou, QV Le, AJ Smola Advances in Neural information Processing Systems NIPS, 1593-1600, 2008 | 507 | 2008 |
| 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 RecSys, 2016 | 456 | 2016 |
| CLiMF: Learning to Maximize Reciprocal Rank with Collaborative Less-is-more Filtering Y Shi, A Karatzoglou, L Baltrunas, M Larson, N Oliver, A Hanjalic Proceedings of the sixth ACM conference on Recommender Systems RecSys, 139-146, 2012 | 415 | 2012 |
| A Simple Convolutional Generative Network for Next Item Recommendation F Yuan, A Karatzoglou, I Arapakis, JM Jose, X He Proceedings of the Twelfth ACM WSDM International Conference on Web Search …, 2019 | 346 | 2019 |
| Collaborative Filtering Bandits S Li, A Karatzoglou, C Gentile Proceedings of the 39th International ACM SIGIR conference on Research and …, 2016 | 338 | 2016 |
| TFMAP: Optimizing MAP for Top-N Context-aware Recommendation Y Shi, A Karatzoglou, L Baltrunas, M Larson, A Hanjalic, N Oliver Proceedings of the 35th international ACM SIGIR conference on Research and …, 2012 | 271 | 2012 |
| kernlab: Kernel-based Machine Learning Lab A Karatzoglou, A Smola, K Hornik The Comprehensive R Archive Network CRAN, 2013 | 242* | 2013 |
| Improving Maximum Margin Matrix Factorization M Weimer, A Karatzoglou, A Smola Machine Learning 72 (3), 263-276, 2008 | 166 | 2008 |
| Coverage, Redundancy and Size-awareness in Genre Diversity for Recommender Systems S Vargas, L Baltrunas, A Karatzoglou, P Castells Proceedings of the 8th ACM Conference on Recommender Systems RecSys, 209-216, 2014 | 162 | 2014 |
| Learning to Rank for Recommender Systems A Karatzoglou, L Baltrunas, Y Shi Proceedings of the 7th ACM conference on Recommender Systems RecSys, 493-494, 2013 | 159 | 2013 |
| Towards a Universal Neural Network Encoder for Time Series J Serrŕ, S Pascual, A Karatzoglou arXiv preprint arXiv:1805.03908, 2018 | 132 | 2018 |
| RecoGym: A Reinforcement Learning Environment for the problem of Product Recommendation in Online Advertising. D Rohde, S Bonner, T Dunlop, F Vasile, A Karatzoglou arXiv preprint arXiv:1808.00720, 2018 | 130 | 2018 |
| On Context-dependent Clustering of Bandits C Gentile, S Li, P Kar, A Karatzoglou, G Zappella, E Etrue Proceedings of the 34th International Conference on Machine Learning ICML 70 …, 2017 | 127 | 2017 |
Balázs HidasiGravity R&DVerified email at gravityrd.com
