| Only Train Once: A One-Shot Neural Network Training And Pruning Framework T Chen, B Ji, T Ding, B Fang, G Wang, Z Zhu, L Liang, Y Shi, S Yi, X Tu Thirty-Fifth Conference on Neural Information Processing Systems, 2021 | 116 | 2021 |
| Generative Adversarial Network for Handwritten Text B Ji, T Chen arXiv 1907 (1907.11845), 2019 | 36 | 2019 |
| OTOV2: Automatic, Generic, User-Friendly T Chen, L Liang, T Ding, Z Zhu, I Zharkov The Eleventh International Conference on Learning Representations, 2023 | 34 | 2023 |
| Orthant Based Proximal Stochastic Gradient Method for -Regularized Optimization T Chen, T Ding, B Ji, G Wang, J Tian, Y Shi, S Yi, X Tu, Z Zhu European Conference on Machine Learning, 2020 | 27* | 2020 |
| A Reduced-Space Algorithm for Minimizing -Regularized Convex Functions T Chen, FE Curtis, DP Robinson SIAM Journal on Optimization 27 (3), 1583-1610, 2017 | 27 | 2017 |
| DistiLLM: Towards Streamlined Distillation for Large Language Models J Ko, S Kim, T Chen, SY Yun Proceedings of the 41th International Conference on Machine Learning, 2024 | 22 | 2024 |
| Lorashear: Efficient large language model structured pruning and knowledge recovery T Chen, T Ding, B Yadav, I Zharkov, L Liang arXiv preprint arXiv:2310.18356, 2023 | 20 | 2023 |
| Evolution of co-operation among mobile agents with different influence Z Wang, T Chen, X Wang, J Jin, M Li Physica A: Statistical Mechanics and its Applications 392 (19), 4655-4662, 2013 | 19 | 2013 |
| Neural network compression via sparse optimization T Chen, B Ji, Y Shi, T Ding, B Fang, S Yi, X Tu arXiv preprint arXiv:2011.04868, 2020 | 17 | 2020 |
| The efficiency spectrum of large language models: An algorithmic survey T Ding, T Chen, H Zhu, J Jiang, Y Zhong, J Zhou, G Wang, Z Zhu, ... arXiv preprint arXiv:2312.00678, 2023 | 15 | 2023 |
| FaRSA for ℓ1-regularized convex optimization: local convergence and numerical experience T Chen, FE Curtis, DP Robinson Optimization Methods and Software 33 (2), 396-415, 2018 | 14 | 2018 |
| Transferable adversarial examples can efficiently fool topic models Z Wang, Y Zheng, H Zhu, C Yang, T Chen Computers & Security 118, 102749, 2022 | 13 | 2022 |
| A Half-Space Stochastic Projected Gradient Method for Group Sparsity Regularization T Chen, G Wang, D Tianyu, B Ji, S Yi, Z Zhu | 12* | 2020 |
| A Fast Reduced-Space Algorithmic Framework for Sparse Optimization T Chen Johns Hopkins University, 2018 | 11 | 2018 |
| OTOv3: Automatic Architecture-Agnostic Neural Network Training and Compression from Structured Pruning to Erasing Operators T Chen, T Ding, Z Zhu, Z Chen, HT Wu, I Zharkov, L Liang arXiv preprint arXiv:2312.09411, 2023 | 8* | 2023 |
| An adaptive half-space projection method for stochastic optimization problems with group sparse regularization Y Dai, T Chen, G Wang, DP Robinson Transactions on machine learning research, 2023 | 8 | 2023 |
| FSCNN: A Fast Sparse Convolution Neural Network Inference System T Chen, Y Shi, S Yi | 8* | 2021 |
| Phase-segregation free quasi-2D perovskite/organic tandem solar cells with low V oc loss and efficiency beyond 21% H Wu, T Chen, Y Li, S Guan, L Zhang, T Chen, Y Liu, Y Jin, L Zuo, W Fu, ... Journal of Materials Chemistry A 11 (13), 6877-6885, 2023 | 7 | 2023 |
| Signature verification T Chen, S Yi US Patent 11,450,150, 2022 | 6* | 2022 |
| Fora: Fast-forward caching in diffusion transformer acceleration P Selvaraju, T Ding, T Chen, I Zharkov, L Liang arXiv preprint arXiv:2407.01425, 2024 | 5 | 2024 |
Tianyu Ding, Ph.D.Principal Researcher, Microsoft | Johns Hopkins University在 microsoft.com 的电子邮件经过验证
