Yuyan Wang
Yuyan Wang
Assistant Professor of Marketing, Stanford Graduate School of Business
Verified email at - Homepage
Cited by
Cited by
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
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
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
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
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
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
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
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
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
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
Food discovery with Uber Eats: recommending for the marketplace
Y Wang, Y Ning, I Liu, XX Zhang
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
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
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
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
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
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
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
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
Recommending for a Multi-Sided Marketplace: A Multi-Objective Hierarchical Approach
Y Wang, L Tao, XX Zhang
Available at SSRN 4602954, 2023
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