| Estimation of high dimensional mean regression in the absence of symmetry and light tail assumptions J Fan, Q Li, Y Wang Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2017 | 239 | 2017 |
| Surrogate for long-term user experience in recommender systems Y Wang, M Sharma, C Xu, S Badam, Q Sun, L Richardson, L Chung, ... Proceedings of the 28th ACM SIGKDD conference on knowledge discovery and …, 2022 | 39 | 2022 |
| Values of user exploration in recommender systems M Chen, Y Wang, C Xu, Y Le, M Sharma, L Richardson, SL Wu, E Chi Proceedings of the 15th ACM Conference on Recommender Systems, 85-95, 2021 | 36 | 2021 |
| Understanding and improving fairness-accuracy trade-offs in multi-task learning Y Wang, X Wang, A Beutel, F Prost, J Chen, EH Chi Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021 | 35 | 2021 |
| Embracing the blessing of dimensionality in factor models Q Li, G Cheng, J Fan, Y Wang Journal of the American Statistical Association 113 (521), 380-389, 2018 | 35 | 2018 |
| A statistical investigation of the dependence of tropical cyclone intensity change on the surrounding environment N Lin, R Jing, Y Wang, E Yonekura, J Fan, L Xue Monthly Weather Review 145 (7), 2813-2831, 2017 | 31 | 2017 |
| Beyond point estimate: Inferring ensemble prediction variation from neuron activation strength in recommender systems Z Chen, Y Wang, D Lin, DZ Cheng, L Hong, EH Chi, C Cui Proceedings of the 14th ACM International Conference on Web Search and Data …, 2021 | 9 | 2021 |
| Food discovery with Uber Eats: recommending for the marketplace Y Wang, Y Ning, I Liu, XX Zhang | 9 | 2021 |
| Can small heads help? understanding and improving multi-task generalization Y Wang, Z Zhao, B Dai, C Fifty, D Lin, L Hong, L Wei, EH Chi Proceedings of the ACM Web Conference 2022, 3009-3019, 2022 | 8 | 2022 |
| Learning to augment for casual user recommendation J Wang, Y Le, B Chang, Y Wang, EH Chi, M Chen Proceedings of the ACM Web Conference 2022, 2183-2194, 2022 | 8 | 2022 |
| Recommending for a multi-sided marketplace with heterogeneous contents Y Wang, L Tao, XX Zhang Proceedings of the 16th ACM Conference on Recommender Systems, 456-459, 2022 | 6 | 2022 |
| Multi-layer optimization for a multi-sided network service Y Wang, XX Zhang, IS Liu, Y Ning, C Peng US Patent 11,127,066, 2021 | 6 | 2021 |
| Optimizing listing efficiency and efficacy for a delivery coordination system XX Zhang, S Zhang, Y Wang, M Gogate, Y Ning, C Peng, I Liu, C Lee US Patent 10,713,318, 2020 | 6 | 2020 |
| Latent user intent modeling for sequential recommenders B Chang, A Karatzoglou, Y Wang, C Xu, EH Chi, M Chen Companion Proceedings of the ACM Web Conference 2023, 427-431, 2023 | 5 | 2023 |
| Prompt tuning large language models on personalized aspect extraction for recommendations P Li, Y Wang, EH Chi, M Chen arXiv preprint arXiv:2306.01475, 2023 | 4 | 2023 |
| Bias-robust Integration of Observational and Experimental Estimators M Oberst, A D’Amour, M Chen, Y Wang, D Sontag, S Yadlowsky arXiv preprint arXiv:2205.10467, 2022 | 3 | 2022 |
| On-demand coordinated comestible item delivery system Nathan Berrebbi, Ferras Hamad, Isaac Liu, Thanh Le Nguyen, Xian Xing Zhang ... US Patent App. 16/059,483, 2019 | 3* | 2019 |
| Food discovery with uber eats: Recommending for the marketplace.(2018) Y Wang, Y Ning, I Liu, XX Zhang URL https://eng. uber. com/uber-eats-recommending-marketplace, 2018 | 3 | 2018 |
| Recommending for a multi-sided marketplace: A multi-objective hierarchical approach Y Wang, L Tao, XX Zhang Available at SSRN 4602954, 2023 | 1 | 2023 |
| Understanding the risks and rewards of combining unbiased and possibly biased estimators, with applications to causal inference M Oberst, A D'Amour, M Chen, Y Wang, D Sontag, S Yadlowsky arXiv preprint arXiv:2205.10467, 2022 | 1 | 2022 |
