| Resnest: Split-attention networks. H Zhang, C Wu, Z Zhang, Y Zhu, Z Zhang, H Lin, Y Sun, T He, J Mueller, ... Conference on Computer Vision and Pattern (ECV), 2022 | 1461 | 2022 |
| Deep Graph Library: Towards Efficient and Scalable Deep Learning on Graphs M Wang, L Yu, Q Gan, D Zheng, Y Gai, Z Ye, M Li, J Zhou, Q Huang, ... International Conference on Learning Representations, 2019 | 639 | 2019 |
| Self-Driving Database Management Systems. A Pavlo, G Angulo, J Arulraj, H Lin, J Lin, L Ma, P Menon, TC Mowry, ... CIDR 4, 1, 2017 | 295 | 2017 |
| GluonCV and GluonNLP: Deep Learning in Computer Vision and Natural Language Processing J Guo, H He, T He, L Lausen, M Li, H Lin, X Shi, C Wang, J Xie, S Zha, ... Journal of Machine Learning Research, 2019 | 194 | 2019 |
| Temporal-Contextual Recommendation in Real-Time Y Ma, BM Narayanaswamy, H Lin, H Ding KDD 2020, 2020 | 61 | 2020 |
| Is Network the Bottleneck of Distributed Training? Z Zhang, C Chang, H Lin, Y Wang, R Arora, X Jin SIGCOMM NetAI, 2020 | 56 | 2020 |
| Local AdaAlter: Communication-Efficient Stochastic Gradient Descent with Adaptive Learning Rates C Xie, O Koyejo, I Gupta, H Lin NeurIPS 2020, optimizations for machine learning, 2019 | 41 | 2019 |
| CSER: Communication-efficient SGD with Error Reset C Xie, S Zheng, OO Koyejo, I Gupta, M Li, H Lin Advances in Neural Information Processing Systems 33, 2020 | 28 | 2020 |
| Dynamic Mini-batch SGD for Elastic Distributed Training: Learning in the Limbo of Resources H Lin, H Zhang, Y Ma, T He, Z Zhang, S Zha, M Li arXiv preprint arXiv:1904.12043, 2019 | 19 | 2019 |
| Accelerated Large Batch Optimization of BERT Pretraining in 54 minutes S Zheng, H Lin, S Zha, M Li arXiv preprint arXiv:2006.13484, 2020 | 18 | 2020 |
| Compressed Communication for Distributed Training: Adaptive Methods and System Y Zhong, C Xie, S Zheng, H Lin arXiv preprint arXiv:2105.07829, 2021 | 6 | 2021 |
| Deep graph library M Wang, L Yu, Q Gan, D Zheng, Y Gai, Z Ye, M Li, J Zhou, Q Huang, ... | 6 | 2018 |
| Hi-Speed DNN Training with Espresso: Unleashing the Full Potential of Gradient Compression with Near-Optimal Usage Strategies Z Wang, H Lin, Y Zhu, TSE Ng Proceedings of the Eighteenth European Conference on Computer Systems, 867-882, 2023 | 5 | 2023 |
| dPRO: A Generic Performance Diagnosis and Optimization Toolkit for Expediting Distributed DNN Training H Hu, C Jiang, Y Zhong, Y Peng, C Wu, Y Zhu, H Lin, C Guo Proceedings of Machine Learning and Systems 4, 623-637, 2022 | 3 | 2022 |
| Just-in-Time Dynamic-Batching S Zha, Z Jiang, H Lin, Z Zhang Conference on Neural Information Processing Systems, 2018 | 3 | 2018 |
| Dive into Deep Learning for Natural Language Processing H Lin, X Shi, L Lausen, A Zhang, H He, S Zha, A Smola Proceedings of the 2019 Conference on Empirical Methods in Natural Language …, 2019 | 2 | 2019 |
| SAPipe: Staleness-Aware Pipeline for Data Parallel DNN Training Y Chen, C Xie, M Ma, J Gu, Y Peng, H Lin, C Wu, Y Zhu Advances in Neural Information Processing Systems 35, 17981-17993, 2022 | 1 | 2022 |
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