| On uni-modal feature learning in supervised multi-modal learning C Du, J Teng, T Li, Y Liu, T Yuan, Y Wang, Y Yuan, H Zhao International Conference on Machine Learning, 8632-8656, 2023 | 102 | 2023 |
| Adversarial Robustness Certificates: a Randomized Smoothing Approach J Teng, GH Lee, Y Yuan | 43 | 2020 |
| Predictive inference with feature conformal prediction J Teng, C Wen, D Zhang, Y Bengio, Y Gao, Y Yuan The Eleventh International Conference on Learning Representations (ICLR 2023), 2022 | 39 | 2022 |
| Fighting fire with fire: Avoiding dnn shortcuts through priming C Wen, J Qian, J Lin, J Teng, D Jayaraman, Y Gao International Conference on Machine Learning (ICML 2022), 23723-23750, 2022 | 25 | 2022 |
| T-sci: A two-stage conformal inference algorithm with guaranteed coverage for cox-mlp J Teng, Z Tan, Y Yuan International Conference on Machine Learning (ICML 2021), 10203-10213, 2021 | 21 | 2021 |
| High-resolution probabilistic load forecasting: A learning ensemble approach C Lu, J Liang, W Jiang, J Teng, C Wu Journal of the Franklin Institute 360 (6), 4272-4296, 2023 | 15 | 2023 |
| Can pretext-based self-supervised learning be boosted by downstream data? a theoretical analysis J Teng, W Huang, H He International conference on artificial intelligence and statistics, 4198-4216, 2022 | 15 | 2022 |
| Benign Overfitting in Classification: Provably Counter Label Noise with Larger Models K Wen, J Teng, J Zhang The Eleventh International Conference on Learning Representations (ICLR 2023), 2022 | 12* | 2022 |
| Towards data-algorithm dependent generalization: a case study on overparameterized linear regression J Xu, J Teng, Y Yuan, A Yao Advances in Neural Information Processing Systems 36, 79698-79733, 2023 | 10* | 2023 |
| Lower generalization bounds for gd and sgd in smooth stochastic convex optimization P Zhang, J Teng, J Zhang arXiv preprint arXiv:2303.10758, 2023 | 9* | 2023 |
| Towards Understanding Generalization via Decomposing Excess Risk Dynamics J Teng, J Ma, Y Yuan ICLR, arXiv preprint arXiv:2106.06153, 2021 | 9 | 2021 |
| Finding Generalization Measures by Contrasting Signal and Noise J Teng, B Zhang, R Li, H He, Y Wang, Y Tian, Y Yuan International Conference on Machine Learning (ICML 2023), 2023 | 2 | 2023 |
| Inject Machine Learning into Significance Test for Misspecified Linear Models J Teng, Y Yuan arXiv preprint arXiv:2006.03167, 2020 | 2 | 2020 |
| What Makes Looped Transformers Perform Better Than Non-Recursive Ones (Provably) Z Gong, Y Liu, J Teng | 1 | 2025 |
| Minimax Optimal Two-Stage Algorithm For Moment Estimation Under Covariate Shift Z Zhang, X Liu, S Wang, J Teng arXiv preprint arXiv:2506.23453, 2025 | 1 | 2025 |
| Theoretical Modeling of LLM Self-Improvement Training Dynamics Through Solver-Verifier Gap Y Sun, Y Liang, Z Zhang, J Teng arXiv preprint arXiv:2507.00075, 2025 | 1 | 2025 |
| Disentangling feature structure: A mathematically provable two-stage training dynamics in transformers Z Gong, S Li, Y Liu, J Teng arXiv preprint arXiv:2502.20681, 2025 | 1 | 2025 |
| Anomaly Detection with Test Time Augmentation and Consistency Evaluation H He, J Teng, Y Yuan arXiv preprint arXiv:2206.02345, 2022 | 1 | 2022 |
| Accelerating Feature Conformal Prediction via Taylor Approximation Z Tang, B Wang, C Wen, J Teng The Thirty-ninth Annual Conference on Neural Information Processing Systems, 0 | 1* | |
| What Makes Looped Transformers Perform Better Than Non-Recursive Ones Z Gong, Y Liu, J Teng arXiv preprint arXiv:2510.10089, 2025 | | 2025 |
Yang YuanTsinghua UniversityVerified email at tsinghua.edu.cn
