| Coevolutionary recommendation model: Mutual learning between ratings and reviews Y Lu, R Dong, B Smyth Proceedings of the 2018 World Wide Web Conference, 773-782, 2018 | 175 | 2018 |
| Faster ridge regression via the subsampled randomized hadamard transform Y Lu, P Dhillon, DP Foster, L Ungar Advances in neural information processing systems 26, 2013 | 154 | 2013 |
| Why I like it: multi-task learning for recommendation and explanation Y Lu, R Dong, B Smyth Proceedings of the 12th ACM Conference on Recommender Systems, 4-12, 2018 | 140 | 2018 |
| Efficient and Information-Preserving Future Frame Prediction and Beyond W Yu, Y Lu, S Easterbrook, S Fidler The 8th International Conference on Learning Representations, ICLR 2020, 2020 | 89 | 2020 |
| Context-aware scene graph generation with seq2seq transformers Y Lu, H Rai, J Chang, B Knyazev, G Yu, S Shekhar, GW Taylor, M Volkovs Proceedings of the IEEE/CVF international conference on computer vision …, 2021 | 72 | 2021 |
| Two-stage model for automatic playlist continuation at scale M Volkovs, H Rai, Z Cheng, G Wu, Y Lu, S Sanner Proceedings of the ACM Recommender Systems Challenge 2018, 1-6, 2018 | 48 | 2018 |
| CrevNet: Conditionally Reversible Video Prediction W Yu, Y Lu, S Easterbrook, S Fidler The NeurIPS 2019 Traffic4cast Workshop, 2019 | 16 | 2019 |
| Multi-view scene graph generation in videos Y Lu, C Chang, H Rai, G Yu, M Volkovs International Challenge on Activity Recognition (ActivityNet) CVPR 2021 …, 2021 | 13 | 2021 |
| Traffic4cast at neurips 2021-temporal and spatial few-shot transfer learning in gridded geo-spatial processes C Eichenberger, M Neun, H Martin, P Herruzo, M Spanring, Y Lu, S Choi, ... NeurIPS 2021 Competitions and Demonstrations Track, 97-112, 2022 | 12 | 2022 |
| Session-based recommendation with transformers Y Lu, Z Gao, Z Cheng, J Sun, B Brown, G Yu, A Wong, F Pérez, M Volkovs Proceedings of the Recommender Systems Challenge 2022, 29-33, 2022 | 11 | 2022 |
| Forecasting the future of artificial intelligence with machine learning-based link prediction in an exponentially growing knowledge network M Krenn, L Buffoni, B Coutinho, S Eppel, JG Foster, A Gritsevskiy, H Lee, ... Nature Machine Intelligence 5 (11), 1326-1335, 2023 | 10 | 2023 |
| Robust contextual models for in-session personalization M Volkovs, A Wong, Z Cheng, F Pérez, I Stanevich, Y Lu Proceedings of the Workshop on ACM Recommender Systems Challenge, 1-5, 2019 | 10 | 2019 |
| Context-aware sentiment detection from ratings Y Lu, R Dong, B Smyth Research and Development in Intelligent Systems XXXIII, 87-101, 2016 | 9 | 2016 |
| Predicting the Future of AI with AI: High-quality link prediction in an exponentially growing knowledge network M Krenn, L Buffoni, B Coutinho, S Eppel, JG Foster, A Gritsevskiy, H Lee, ... arXiv preprint arXiv:2210.00881, 2022 | 8 | 2022 |
| Convolutional matrix factorization for recommendation explanation Y Lu, R Dong, B Smyth Proceedings of the 23rd International Conference on Intelligent User …, 2018 | 8 | 2018 |
| Learning Effective Visual Relationship Detector on 1 GPU Y Lu, C Chang, H Rai, G Yu, M Volkovs The ICCV 2019 Open Images Workshop, 2019 | 7 | 2019 |
| Predicting research trends in artificial intelligence with gradient boosting decision trees and time-aware graph neural networks Y Lu 2021 IEEE International Conference on Big Data (Big Data), 5809-5814, 2021 | 4 | 2021 |
| Learning to Transfer for Traffic Forecasting via Multi-task Learning Y Lu The NeurIPS 2021 Traffic4cast Workshop, 2021 | 4 | 2021 |
| Traffic4cast at NeurIPS 2022–Predict dynamics along graph edges from sparse node data: Whole city traffic and ETA from stationary vehicle detectors M Neun, C Eichenberger, H Martin, M Spanring, R Siripurapu, D Springer, ... NeurIPS 2022 Competition Track, 251-278, 2022 | 3 | 2022 |
| Robust User Engagement Modeling With Transformers and Self Supervision Y Lu, M Volkovs Proceedings of the Recommender Systems Challenge 2023, 23-27, 2023 | | 2023 |
Maksims VolkovsLayer 6 AIcs.toronto.edu의 이메일 확인됨
