ARSM: Augment-REINFORCE-swap-merge estimator for gradient backpropagation through categorical variables M Yin, Y Yue, M Zhou International Conference on Machine Learning, 7095-7104, 2019 | 36 | 2019 |
Semi-supervised learning using adversarial training with good and bad samples W Li, Z Wang, Y Yue, J Li, W Speier, M Zhou, C Arnold Machine Vision and Applications 31, 1-11, 2020 | 25 | 2020 |
On hyperparameter tuning in general clustering problemsm X Fan, Y Yue, P Sarkar, YXR Wang International conference on machine learning, 2996-3007, 2020 | 21 | 2020 |
Clinical implications of the T790M mutation in disease characteristics and treatment response in patients with epidermal growth factor receptor (EGFR)-mutated non–small-cell … D Gaut, MS Sim, Y Yue, BR Wolf, PA Abarca, JM Carroll, JW Goldman, ... Clinical lung cancer 19 (1), e19-e28, 2018 | 20 | 2018 |
Implicit distributional reinforcement learning Y Yue, Z Wang, M Zhou Advances in Neural Information Processing Systems 33, 7135-7147, 2020 | 14 | 2020 |
Discrete action on-policy learning with action-value critic Y Yue, Y Tang, M Yin, M Zhou International Conference on Artificial Intelligence and Statistics, 1977-1987, 2020 | 7 | 2020 |
Learning to Rank For Push Notifications Using Pairwise Expected Regret Y Yue, Y Xie, H Wu, H Jia, S Zhai, W Shi, JJ Hunt arXiv preprint arXiv:2201.07681, 2022 | 4 | 2022 |
A unified framework for tuning hyperparameters in clustering problems X Fan, Y Yue, P Sarkar, YX Wang arXiv preprint arXiv:1910.08018, 2019 | 4 | 2019 |
T-optimal designs for multi-factor polynomial regression models via a semidefinite relaxation method Y Yue, L Vandenberghe, WK Wong Statistics and Computing 29, 725-738, 2019 | 3 | 2019 |
Boosting deep reinforcement learning algorithms with deep probabilistic models Y Yue | | 2021 |
T-optimal designs formulti-factor polynomial regressionmodelsvia a semidefinite Y Yue, L Vandenberghe, WK Wong | | 2018 |
S1 Additional theoretical results and proofs in Sec-tion 3 X Fan, YXR Wang, P Sarkar, Y Yue | | |