| Understanding convolutional neural networks for text classification A Jacovi, OS Shalom, Y Goldberg arXiv preprint arXiv:1809.08037, 2018 | 314 | 2018 |
| Rank and rate: multi-task learning for recommender systems G Hadash, OS Shalom, R Osadchy Proceedings of the 12th ACM Conference on Recommender Systems, 451-454, 2018 | 64 | 2018 |
| Beyond collaborative filtering: The list recommendation problem O Sar Shalom, N Koenigstein, U Paquet, HP Vanchinathan Proceedings of the 25th international conference on world wide web, 63-72, 2016 | 53 | 2016 |
| Enhanced Mean Retrieval Score Estimation for Query Performance Prediction H Roitman, S Erera, O Sar Shalom, B Weiner Proceedings of the ACM SIGIR International Conference on Theory of …, 2017 | 33 | 2017 |
| A black-box attack model for visually-aware recommender systems R Cohen, O Sar Shalom, D Jannach, A Amir Proceedings of the 14th ACM International Conference on Web Search and Data …, 2021 | 31 | 2021 |
| Data quality matters in recommender systems O Sar Shalom, S Berkovsky, R Ronen, E Ziklik, A Amihood Proceedings of the 9th ACM Conference on Recommender Systems, 257-260, 2015 | 30 | 2015 |
| Bruce: Bundle recommendation using contextualized item embeddings T Avny Brosh, A Livne, O Sar Shalom, B Shapira, M Last Proceedings of the 16th ACM Conference on Recommender Systems, 237-245, 2022 | 27 | 2022 |
| Towards More Impactful Recommender Systems Research. D Jannach, OS Shalom, JA Konstan ImpactRS@ RecSys, 2019 | 26 | 2019 |
| Privacy and fairness in recommender systems via adversarial training of user representations YS Resheff, Y Elazar, M Shahar, OS Shalom arXiv preprint arXiv:1807.03521, 2018 | 25 | 2018 |
| Word Emphasis Prediction for Expressive Text to Speech Y Mass, S Shechtman, M Mordechay, R Hoory, O Sar Shalom, G Lev, ... Interspeech 2018, 2868-2872, 2018 | 23 | 2018 |
| RecSys' 16 workshop on deep learning for recommender systems (DLRS) A Karatzoglou, B Hidasi, D Tikk, O Sar-Shalom, H Roitman, B Shapira, ... Proceedings of the 10th ACM Conference on Recommender Systems, 415-416, 2016 | 20 | 2016 |
| A generative model for review-based recommendations OS Shalom, G Uziel, A Kantor Proceedings of the 13th ACM conference on recommender systems, 353-357, 2019 | 17 | 2019 |
| Dlrs 2017: Second workshop on deep learning for recommender systems B Hidasi, A Karatzoglou, O Sar-Shalom, S Dieleman, B Shapira, D Tikk Proceedings of the Eleventh ACM Conference on Recommender Systems, 370-371, 2017 | 11 | 2017 |
| Are all rejected recommendations equally bad? towards analysing rejected recommendations S Frumerman, G Shani, B Shapira, O Sar Shalom Proceedings of the 27th ACM Conference on User Modeling, Adaptation and …, 2019 | 10 | 2019 |
| Understanding convolutional neural networks for text classification. arXiv 2018 A Jacovi, OS Shalom, Y Goldberg arXiv preprint arXiv:1809.08037, 0 | 10 | |
| Natural language processing for recommender systems OS Shalom, H Roitman, P Kouki Recommender Systems Handbook, 447-483, 2021 | 9 | 2021 |
| Multiply Balanced k −Partitioning A Amir, J Ficler, R Krauthgamer, L Roditty, O Sar Shalom Latin American Symposium on Theoretical Informatics, 586-597, 2014 | 9 | 2014 |
| Semi-supervised Adversarial Learning for Complementary Item Recommendation K Bibas, O Sar Shalom, D Jannach Proceedings of the ACM Web Conference 2023, 1804-1812, 2023 | 8 | 2023 |
| Unsupervised anomaly detection using generative adversarial networks G Lev, M Ninio, OS Shalom US Patent App. 15/813,192, 2019 | 8 | 2019 |
| Extracting customer problem description from call transcripts N Haas, A Zicharevich, OS Shalom, A Shalev US Patent 11,423,900, 2022 | 7 | 2022 |
