APE: Argument pair extraction from peer review and rebuttal via multi-task learning L Cheng, L Bing, Q Yu, W Lu, L Si Proceedings of the 2020 Conference on Empirical Methods in Natural Language …, 2020 | 56 | 2020 |
Review-aware answer prediction for product-related questions incorporating aspects Q Yu, W Lam Proceedings of the Eleventh ACM International Conference on Web Search and …, 2018 | 42 | 2018 |
Responding e-commerce product questions via exploiting qa collections and reviews Q Yu, W Lam, Z Wang Proceedings of the 27th International Conference on Computational …, 2018 | 19 | 2018 |
IAM: A Comprehensive and Large-Scale Dataset for Integrated Argument Mining Tasks L Cheng, L Bing, R He, Q Yu, Y Zhang, L Si Proceedings of the 60th Annual Meeting of the Association for Computational …, 2022 | 18 | 2022 |
Review-based Question Generation with Adaptive Instance Transfer and Augmentation Q Yu, L Bing, Q Zhang, W Lam, L Si Proceedings of the 58th Annual Meeting of the Association for Computational …, 2020 | 18* | 2020 |
Decoder-only or encoder-decoder? interpreting language model as a regularized encoder-decoder Z Fu, W Lam, Q Yu, AMC So, S Hu, Z Liu, N Collier arXiv preprint arXiv:2304.04052, 2023 | 16 | 2023 |
Alleviating cold-start problem in CTR prediction with a variational embedding learning framework X Xu, C Yang, Q Yu, Z Fang, J Wang, C Fan, Y He, C Peng, Z Lin, J Shao Proceedings of the ACM Web Conference 2022, 27-35, 2022 | 14 | 2022 |
Data augmentation based on adversarial autoencoder handling imbalance for learning to rank Q Yu, W Lam Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 411-418, 2019 | 12 | 2019 |
Exploiting interactions of review text, hidden user communities and item groups, and time for collaborative filtering Y Xu, Q Yu, W Lam, T Lin Knowledge and Information Systems 52, 221-254, 2017 | 10 | 2017 |
Product question intent detection using indicative clause attention and adversarial learning Q Yu, W Lam Proceedings of the 2018 ACM SIGIR International Conference on Theory of …, 2018 | 9 | 2018 |
Product question answering in e-commerce: A survey Y Deng, W Zhang, Q Yu, W Lam arXiv preprint arXiv:2302.08092, 2023 | 8 | 2023 |
Enhancing drug–drug interaction prediction by three-way decision and knowledge graph embedding X Hao, Q Chen, H Pan, J Qiu, Y Zhang, Q Yu, Z Han, X Du Granular Computing 8 (1), 67-76, 2023 | 7 | 2023 |
Answering product-related questions with heterogeneous information W Zhang, Q Yu, W Lam Proceedings of the 1st Conference of the Asia-Pacific Chapter of the …, 2020 | 4 | 2020 |
Rényi divergence based generalization for learning of classification restricted Boltzmann machines Q Yu, Y Hou, X Zhao, G Cheng 2014 IEEE International Conference on Data Mining Workshop, 692-697, 2014 | 4 | 2014 |
An incremental update framework for online recommenders with data-driven prior C Yang, J Chen, Q Yu, X Wu, K Ma, Z Zhao, Z Fang, W Chen, C Fan, J He, ... Proceedings of the 32nd ACM International Conference on Information and …, 2023 | 2 | 2023 |
Gating-adapted Wavelet Multiresolution Analysis for Exposure Sequence Modeling in CTR prediction X Xu, Z Fang, Q Yu, R Huang, Y Li, Y He, C Peng, Z Lin, J Shao Proceedings of the 45th International ACM SIGIR conference on Research and …, 2022 | 2 | 2022 |
A distribution separation method using irrelevance feedback data for information retrieval P Zhang, Q Yu, Y Hou, D Song, J Li, B Hu ACM Transactions on Intelligent Systems and Technology (TIST) 8 (3), 1-26, 2017 | 2 | 2017 |
Document Boltzmann machines for information retrieval Q Yu, P Zhang, Y Hou, D Song, J Wang Advances in Information Retrieval: 37th European Conference on IR Research …, 2015 | 2 | 2015 |
Generalized analysis of a distribution separation method P Zhang, Q Yu, Y Hou, D Song, J Li, B Hu Entropy 18 (4), 105, 2016 | 1 | 2016 |
Understanding boltzmann machine and deep learning via a confident information first principle X Zhao, Y Hou, Q Yu, D Song, W Li arXiv preprint arXiv:1302.3931, 2013 | 1 | 2013 |