| MaxUp: Lightweight Adversarial Training With Data Augmentation Improves Neural Network Training C Gong, T Ren, M Ye, Q Liu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 98* | 2021 |
| Reward shaping via meta-learning H Zou, T Ren, D Yan, H Su, J Zhu arXiv preprint arXiv:1901.09330, 2019 | 76* | 2019 |
| Learning to write stylized chinese characters by reading a handful of examples D Sun, T Ren, C Li, H Su, J Zhu arXiv preprint arXiv:1712.06424, 2017 | 61 | 2017 |
| Function space particle optimization for Bayesian neural networks Z Wang, T Ren, J Zhu, B Zhang arXiv preprint arXiv:1902.09754, 2019 | 50 | 2019 |
| Accountable off-policy evaluation with kernel bellman statistics Y Feng, T Ren, Z Tang, Q Liu International Conference on Machine Learning, 3102-3111, 2020 | 33 | 2020 |
| Nearly horizon-free offline reinforcement learning T Ren, J Li, B Dai, SS Du, S Sanghavi Advances in neural information processing systems 34, 15621-15634, 2021 | 30 | 2021 |
| Unsupervised Out-of-Domain Detection via Pre-trained Transformers K Xu, T Ren, S Zhang, Y Feng, C Xiong arXiv preprint arXiv:2106.00948, 2021 | 20 | 2021 |
| Implicit regularization and convergence for weight normalization X Wu, E Dobriban, T Ren, S Wu, Z Li, S Gunasekar, R Ward, Q Liu Advances in Neural Information Processing Systems 33, 2835-2847, 2020 | 17* | 2020 |
| Making Linear MDPs Practical via Contrastive Representation Learning T Zhang, T Ren, M Yang, J Gonzalez, D Schuurmans, B Dai International Conference on Machine Learning, 26447-26466, 2022 | 15 | 2022 |
| Lazy-CFR: fast and near optimal regret minimization for extensive games with imperfect information Y Zhou, T Ren, J Li, D Yan, J Zhu arXiv preprint arXiv:1810.04433, 2018 | 12* | 2018 |
| Hierarchical sliced Wasserstein distance K Nguyen, T Ren, H Nguyen, L Rout, T Nguyen, N Ho arXiv preprint arXiv:2209.13570, 2022 | 11 | 2022 |
| A free lunch from the noise: Provable and practical exploration for representation learning T Ren, T Zhang, C Szepesvári, B Dai Uncertainty in Artificial Intelligence, 1686-1696, 2022 | 10 | 2022 |
| Linear bandit algorithms with sublinear time complexity S Yang, T Ren, S Shakkottai, E Price, IS Dhillon, S Sanghavi International Conference on Machine Learning, 25241-25260, 2022 | 9 | 2022 |
| Stein self-repulsive dynamics: Benefits from past samples M Ye, T Ren, Q Liu Advances in Neural Information Processing Systems 33, 241-252, 2020 | 9 | 2020 |
| Spectral Decomposition Representation for Reinforcement Learning T Ren, T Zhang, L Lee, JE Gonzalez, D Schuurmans, B Dai arXiv preprint arXiv:2208.09515, 2022 | 7 | 2022 |
| Towards statistical and computational complexities of Polyak step size gradient descent T Ren, F Cui, A Atsidakou, S Sanghavi, N Ho International Conference on Artificial Intelligence and Statistics, 3930-3961, 2022 | 7 | 2022 |
| Scalable quasi-bayesian inference for instrumental variable regression Z Wang, Y Zhou, T Ren, J Zhu Advances in Neural Information Processing Systems 34, 10469-10482, 2021 | 7 | 2021 |
| Policy Learning for Robust Markov Decision Process with a Mismatched Generative Model J Li, T Ren, D Yan, H Su, J Zhu arXiv preprint arXiv:2203.06587, 2022 | 4 | 2022 |
| Exploration Analysis in Finite-Horizon Turn-based Stochastic Games J Li, Y Zhou, T Ren, J Zhu Conference on Uncertainty in Artificial Intelligence, 201-210, 2020 | 3 | 2020 |
| Markovian Sliced Wasserstein Distances: Beyond Independent Projections K Nguyen, T Ren, N Ho arXiv preprint arXiv:2301.03749, 2023 | 2 | 2023 |
Jun ZhuProfessor of Computer Science, Tsinghua UniversityVerified email at mail.tsinghua.edu.cn
