| Alpaca: Intermittent execution without checkpoints K Maeng, A Colin, B Lucia Proceedings of the ACM on Programming Languages 1 (OOPSLA), 1-30, 2017 | 235 | 2017 |
| Intermittent computing: Challenges and opportunities B Lucia, V Balaji, A Colin, K Maeng, E Ruppel 2nd Summit on Advances in Programming Languages (SNAPL 2017), 2017 | 175 | 2017 |
| Adaptive dynamic checkpointing for safe efficient intermittent computing K Maeng, B Lucia 13th USENIX Symposium on Operating Systems Design and Implementation (OSDI …, 2018 | 161 | 2018 |
| Sustainable ai: Environmental implications, challenges and opportunities CJ Wu, R Raghavendra, U Gupta, B Acun, N Ardalani, K Maeng, G Chang, ... Proceedings of Machine Learning and Systems 4, 795-813, 2022 | 131 | 2022 |
| Supporting peripherals in intermittent systems with just-in-time checkpoints K Maeng, B Lucia Proceedings of the 40th ACM SIGPLAN Conference on Programming Language …, 2019 | 87 | 2019 |
| Adaptive low-overhead scheduling for periodic and reactive intermittent execution K Maeng, B Lucia Proceedings of the 41st ACM SIGPLAN Conference on Programming Language …, 2020 | 54 | 2020 |
| Dynamic task-based intermittent execution for energy-harvesting devices AY Majid, CD Donne, K Maeng, A Colin, KS Yildirim, B Lucia, ... ACM Transactions on Sensor Networks (TOSN) 16 (1), 1-24, 2020 | 33 | 2020 |
| Carbon explorer: A holistic framework for designing carbon aware datacenters B Acun, B Lee, F Kazhamiaka, K Maeng, U Gupta, M Chakkaravarthy, ... Proceedings of the 28th ACM International Conference on Architectural …, 2023 | 24 | 2023 |
| Understanding and improving failure tolerant training for deep learning recommendation with partial recovery K Maeng, S Bharuka, I Gao, M Jeffrey, V Saraph, BY Su, C Trippel, J Yang, ... Proceedings of Machine Learning and Systems 3, 637-651, 2021 | 15 | 2021 |
| Towards fair federated recommendation learning: Characterizing the inter-dependence of system and data heterogeneity K Maeng, H Lu, L Melis, J Nguyen, M Rabbat, CJ Wu Proceedings of the 16th ACM Conference on Recommender Systems, 156-167, 2022 | 10 | 2022 |
| A holistic approach for designing carbon aware datacenters B Acun, B Lee, K Maeng, M Chakkaravarthy, U Gupta, D Brooks, CJ Wu arXiv preprint arXiv:2201.10036, 2022 | 7 | 2022 |
| GPU-based Private Information Retrieval for On-Device Machine Learning Inference M Lam, J Johnson, W Xiong, K Maeng, U Gupta, M Rhu, HHS Lee, ... arXiv preprint arXiv:2301.10904, 2023 | 4 | 2023 |
| Fel: High capacity learning for recommendation and ranking via federated ensemble learning M Hejazinia, D Huba, I Leontiadis, K Maeng, M Malek, L Melis, I Mironov, ... arXiv preprint arXiv:2206.03852, 2022 | 4 | 2022 |
| Cocktail party attack: Breaking aggregation-based privacy in federated learning using independent component analysis S Kariyappa, C Guo, K Maeng, W Xiong, GE Suh, MK Qureshi, HHS Lee International Conference on Machine Learning, 15884-15899, 2023 | 3 | 2023 |
| An architectural charge management interface for energy-harvesting systems E Ruppel, M Surbatovich, H Desai, K Maeng, B Lucia 2022 55th IEEE/ACM International Symposium on Microarchitecture (MICRO), 318-335, 2022 | 3 | 2022 |
| Green Federated Learning A Yousefpour, S Guo, A Shenoy, S Ghosh, P Stock, K Maeng, SW Krüger, ... arXiv preprint arXiv:2303.14604, 2023 | 2 | 2023 |
| Carbon Dependencies in Datacenter Design and Management B Acun, B Lee, F Kazhamiaka, A Sundarrajan, K Maeng, ... HotCarbon, 2022 | 2 | 2022 |
| Bounding the Invertibility of Privacy-preserving Instance Encoding using Fisher Information K Maeng, C Guo, S Kariyappa, GE Suh arXiv preprint arXiv:2305.04146, 2023 | 1 | 2023 |
| Measuring and Controlling Split Layer Privacy Leakage Using Fisher Information K Maeng, C Guo, S Kariyappa, E Suh arXiv preprint arXiv:2209.10119, 2022 | 1 | 2022 |
| Approximating ReLU on a Reduced Ring for Efficient MPC-based Private Inference K Maeng, GE Suh arXiv preprint arXiv:2309.04875, 2023 | | 2023 |
