| Deep multi-interest network for click-through rate prediction Z Xiao, L Yang, W Jiang, Y Wei, Y Hu, H Wang Proceedings of the 29th ACM International Conference on Information …, 2020 | 100 | 2020 |
| Modeling dynamic heterogeneous network for link prediction using hierarchical attention with temporal rnn H Xue, L Yang, W Jiang, Y Wei, Y Hu, Y Lin Machine Learning and Knowledge Discovery in Databases: European Conference …, 2021 | 84 | 2021 |
| Dynamic heterogeneous graph embedding using hierarchical attentions L Yang, Z Xiao, W Jiang, Y Wei, Y Hu, H Wang Advances in Information Retrieval: 42nd European Conference on IR Research …, 2020 | 58 | 2020 |
| An introduction to signal processing for singing-voice analysis: High notes in the effort to automate the understanding of vocals in music EJ Humphrey, S Reddy, P Seetharaman, A Kumar, RM Bittner, ... IEEE Signal Processing Magazine 36 (1), 82-94, 2018 | 53 | 2018 |
| Multiplex bipartite network embedding using dual hypergraph convolutional networks H Xue, L Yang, V Rajan, W Jiang, Y Wei, Y Lin Proceedings of the Web Conference 2021, 1649-1660, 2021 | 42 | 2021 |
| Probabilistic transcription of sung melody using a pitch dynamic model L Yang, A Maezawa, JBL Smith, E Chew 2017 IEEE International Conference on Acoustics, Speech and Signal …, 2017 | 30 | 2017 |
| The filter diagonalisation method for music signal analysis: frame-wise vibrato detection and estimation L Yang, KZ Rajab, E Chew Journal of Mathematics and Music 11 (1), 42-60, 2017 | 25 | 2017 |
| Vibrato Performance Style: A Case Study Comparing Erhu and Violin LYECKZ Rajab In Proc. of the 10th International Conference on Computer Music …, 2013 | 20* | 2013 |
| AVA: An interactive system for visual and quantitative analyses of vibrato and portamento performance styles L Yang, SK Rajab, E Chew | 18 | 2016 |
| Computational modelling and analysis of vibrato and portamento in expressive music performance L Yang Queen Mary University of London, 2017 | 17 | 2017 |
| Vibrato characteristics and frequency histogram envelopes in Beijing opera singing L Yang, M Tian, E Chew | 12 | 2015 |
| Logistic modeling of note transitions L Yang, E Chew, KZ Rajab International Conference on Mathematics and Computation in Music, 161-172, 2015 | 8 | 2015 |
| Human papillomavirus type-16 DNA integration in nuclear matrix and chromosome scaffold associated DNA in a cervical-carcinoma cell-line YF YAM, EC Chew, L Yang, SB CHENGCHEW, MX Ding Oncology Reports 2 (6), 1093-1096, 1995 | 4 | 1995 |
| Deep Evolutional Instant Interest Network for CTR Prediction in Trigger-Induced Recommendation Z Xiao, L Yang, T Zhang, W Jiang, W Ning, Y Yang Proceedings of the 17th ACM International Conference on Web Search and Data …, 2024 | 3 | 2024 |
| Cross-cultural comparisons of experssivity in recorded erhu and violin music: Performer vibrato styles L Yang, E Chew, SK Rajab | 3 | 2014 |
| On Practical Diversified Recommendation with Controllable Category Diversity Framework T Zhang, L Yang, Z Xiao, W Jiang, W Ning Companion Proceedings of the ACM on Web Conference 2024, 255-263, 2024 | 2 | 2024 |
| AVA: A Graphical User Interface for Automatic Vibrato and Portamento Detection and Analysis L Yang, KZ Rajab, E Chew The 42nd International Computer Music Conference, 547--550, 2016 | 1 | 2016 |
| Conditional Potential User Mining framework via explainable surrogate models Y Zhao, Y Xu, Y Liu, L Yang, W Jiang, W Ning, X Sun, L Cui Expert Systems with Applications 262, 125587, 2025 | | 2025 |
| Modeling User Intent Beyond Trigger: Incorporating Uncertainty for Trigger-Induced Recommendation J Ma, Z Xiao, L Yang, H Xue, X Liu, W Jiang, W Ning, G Zhang Proceedings of the 33rd ACM International Conference on Information and …, 2024 | | 2024 |
| MLoRA: Multi-Domain Low-Rank Adaptive Network for CTR Prediction Z Yang, H Gao, D Gao, L Yang, L Yang, X Cai, W Ning, G Zhang Proceedings of the 18th ACM Conference on Recommender Systems, 287-297, 2024 | | 2024 |
Zhibo XiaoAlibaba GroupAdresă de e-mail confirmată pe alibaba-inc.com
