| 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 | 1736 | 2004 |
| Session-based Recommendations with Recurrent Neural Networks B Hidasi, A Karatzoglou, L Baltrunas, D Tikk International Conference on Learning Representations (ICLR) 2016, 2015 | 1316 | 2015 |
| 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 | 893 | 2010 |
| Support Vector Machines in R A Karatzoglou, D Meyer, K Hornik Journal of Statistical Software 15 (09), 1–28, 2006 | 672* | 2006 |
| 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 | 477 | 2008 |
| 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 | 373 | 2012 |
| 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 | 348 | 2017 |
| Recurrent Neural Networks with Top-k Gains for Session-based Recommendations B Hidasi, A Karatzoglou Proceedings of the 27th ACM International Conference on Information and …, 2017 | 327 | 2017 |
| 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 | 307 | 2016 |
| Overcoming Catastrophic Forgetting with Hard Attention to the Task J Serrà, D Surís, M Miron, A Karatzoglou Proceedings of the 35th International Conference on Machine Learning (ICML), 2018 | 305 | 2018 |
| Collaborative Filtering Bandits S Li, A Karatzoglou, C Gentile Proceedings of the 39th International ACM SIGIR conference on Research and …, 2016 | 257 | 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 | 256 | 2012 |
| kernlab: Kernel-based Machine Learning Lab A Karatzoglou, A Smola, K Hornik The Comprehensive R Archive Network (CRAN), 2013 | 182* | 2013 |
| A Simple Convolutional Generative Network for Next Item Recommendation F Yuan, A Karatzoglou, I Arapakis, JM Jose, X He Proceedings of the Twelfth ACM International Conference on Web Search and …, 2019 | 162 | 2019 |
| Improving Maximum Margin Matrix Factorization M Weimer, A Karatzoglou, A Smola Machine Learning 72 (3), 263-276, 2008 | 155 | 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 | 118 | 2014 |
| Climbing the App Wall: Enabling Mobile App Discovery Through Context-aware Recommendations A Karatzoglou, L Baltrunas, K Church, M Böhmer Proceedings of the 21st ACM International Conference on Information and …, 2012 | 118 | 2012 |
| 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 | 113 | 2013 |
| An Approach to Water Supply Clusters by Semi-supervised Learning M Herrera, S Canu, A Karatzoglou, R Pérez-García, J Izquierdo Proceedings of International Environmental Modelling and Software Society …, 2010 | 90 | 2010 |
| 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 …, 2017 | 89 | 2017 |
Linas BaltrunasNetflixVerifierad e-postadress på netflix.com
