| Parallel deep convolutional neural network training by exploiting the overlapping of computation and communication S Lee, D Jha, A Agrawal, A Choudhary, W Liao 2017 IEEE 24th international conference on high performance computing (HiPC …, 2017 | 39 | 2017 |
| Ssfl: Tackling label deficiency in federated learning via personalized self-supervision C He, Z Yang, E Mushtaq, S Lee, M Soltanolkotabi, S Avestimehr arXiv preprint arXiv:2110.02470, 2021 | 29 | 2021 |
| Improving scalability of parallel CNN training by adjusting mini-batch size at run-time S Lee, Q Kang, S Madireddy, P Balaprakash, A Agrawal, A Choudhary, ... 2019 IEEE International Conference on Big Data (Big Data), 830-839, 2019 | 28 | 2019 |
| Layer-wise adaptive model aggregation for scalable federated learning S Lee, T Zhang, AS Avestimehr Proceedings of the AAAI Conference on Artificial Intelligence 37 (7), 8491-8499, 2023 | 23 | 2023 |
| Fedaudio: A federated learning benchmark for audio tasks T Zhang, T Feng, S Alam, S Lee, M Zhang, SS Narayanan, S Avestimehr ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023 | 19 | 2023 |
| Improving all-to-many personalized communication in two-phase i/o Q Kang, R Ross, R Latham, S Lee, A Agrawal, A Choudhary, W Liao SC20: International Conference for High Performance Computing, Networking …, 2020 | 15 | 2020 |
| Improving mpi collective i/o for high volume non-contiguous requests with intra-node aggregation Q Kang, S Lee, K Hou, R Ross, A Agrawal, A Choudhary, W Liao IEEE Transactions on Parallel and Distributed Systems 31 (11), 2682-2695, 2020 | 13 | 2020 |
| Federated learning of large models at the edge via principal sub-model training Y Niu, S Prakash, S Kundu, S Lee, S Avestimehr arXiv preprint arXiv:2208.13141, 2022 | 12 | 2022 |
| Communication-efficient parallelization strategy for deep convolutional neural network training S Lee, A Agrawal, P Balaprakash, A Choudhary, WK Liao 2018 IEEE/ACM Machine Learning in HPC Environments (MLHPC), 47-56, 2018 | 11 | 2018 |
| Evaluation of K-means data clustering algorithm on Intel Xeon Phi S Lee, W Liao, A Agrawal, N Hardavellas, A Choudhary 2016 IEEE International Conference on Big Data (Big Data), 2251-2260, 2016 | 11 | 2016 |
| TimelyFL: Heterogeneity-aware Asynchronous Federated Learning with Adaptive Partial Training T Zhang, L Gao, S Lee, M Zhang, S Avestimehr Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 9 | 2023 |
| Parallel community detection algorithm using a data partitioning strategy with pairwise subdomain duplication D Palsetia, W Hendrix, S Lee, A Agrawal, W Liao, A Choudhary High Performance Computing: 31st International Conference, ISC High …, 2016 | 9 | 2016 |
| Partial model averaging in federated learning: Performance guarantees and benefits S Lee, AK Sahu, C He, S Avestimehr Neurocomputing 556, 126647, 2023 | 7 | 2023 |
| Probing oxygen vacancy distribution in oxide heterostructures by deep Learning-based spectral analysis of current noise S Lee, J Jeon, H Lee Applied Surface Science 604, 154599, 2022 | 7 | 2022 |
| A case study on parallel HDF5 dataset concatenation for high energy physics data analysis S Lee, K Hou, K Wang, S Sehrish, M Paterno, J Kowalkowski, Q Koziol, ... Parallel Computing 110, 102877, 2022 | 7 | 2022 |
| Variance-aware weight quantization of multi-level resistive switching devices based on Pt/LaAlO3/SrTiO3 heterostructures S Lee, J Jeon, K Eom, C Jeong, Y Yang, JY Park, CB Eom, H Lee Scientific Reports 12 (1), 9068, 2022 | 5 | 2022 |
| In situ compression artifact removal in scientific data using deep transfer learning and experience replay S Madireddy, JH Park, S Lee, P Balaprakash, S Yoo, W Liao, CD Hauck, ... Machine Learning: Science and Technology 2 (2), 025010, 2020 | 5 | 2020 |
| Communication-Efficient Local Stochastic Gradient Descent for Scalable Deep Learning S Lee, Q Kang, A Agrawal, A Choudhary, W Liao 2020 IEEE International Conference on Big Data (Big Data), 718-727, 2020 | 5 | 2020 |
| FedML Parrot: A scalable federated learning system via heterogeneity-aware scheduling on sequential and hierarchical training Z Tang, X Chu, RY Ran, S Lee, S Shi, Y Zhang, Y Wang, AQ Liang, ... arXiv preprint arXiv:2303.01778, 2023 | 4 | 2023 |
| Achieving small-batch accuracy with large-batch scalability via Hessian-aware learning rate adjustment S Lee, C He, S Avestimehr Neural Networks 158, 1-14, 2023 | 4 | 2023 |
Wei-keng LiaoNorthwestern UniversityVerified email at eecs.northwestern.edu
