| Making ai less" thirsty": Uncovering and addressing the secret water footprint of ai models P Li, J Yang, MA Islam, S Ren arXiv preprint arXiv:2304.03271, 2023 | 48 | 2023 |
| Automating deep neural network model selection for edge inference B Lu, J Yang, LY Chen, S Ren 2019 IEEE First International Conference on Cognitive Machine Intelligence …, 2019 | 28 | 2019 |
| One proxy device is enough for hardware-aware neural architecture search B Lu, J Yang, W Jiang, Y Shi, S Ren Proceedings of the ACM on Measurement and Analysis of Computing Systems 5 (3 …, 2021 | 22 | 2021 |
| Increasing trustworthiness of deep neural networks via accuracy monitoring Z Shao, J Yang, S Ren arXiv preprint arXiv:2007.01472, 2020 | 13 | 2020 |
| Calibrating deep neural network classifiers on out-of-distribution datasets Z Shao, J Yang, S Ren arXiv preprint arXiv:2006.08914, 2020 | 11 | 2020 |
| Robust bandit learning with imperfect context J Yang, S Ren Proceedings of the AAAI Conference on Artificial Intelligence 35 (12), 10594 …, 2021 | 9 | 2021 |
| Correlation based adaptive compressed sensing for millimeter wave channel estimation J Yang, Z Wei, X Zhang, N Li, L Sang 2017 IEEE Wireless Communications and Networking Conference (WCNC), 1-6, 2017 | 8 | 2017 |
| Enhanced multi-resolution hierarchical codebook design for adaptive compressed sensing based millimeter wave channel estimation J Yang, Z Wei, N Li, L Sang, P Li 2016 IEEE/CIC International Conference on Communications in China (ICCC), 1-5, 2016 | 8 | 2016 |
| Bandit learning with predicted context: Regret analysis and selective context query J Yang, S Ren IEEE INFOCOM 2021-IEEE Conference on Computer Communications, 1-10, 2021 | 7 | 2021 |
| Making AI Less P Li, J Yang, MA Islam, S Ren Thirsty”: Uncovering and Addressing the Secret Water Footprint of AI Models …, 2023 | 6 | 2023 |
| Expert-Calibrated Learning for Online Optimization with Switching Costs P Li*, J Yang*, S Ren Proceedings of the ACM on Measurement and Analysis of Computing Systems 6 (2 …, 2022 | 5 | 2022 |
| Multi-feedback bandit learning with probabilistic contexts L Yang, J Yang, S Ren Proceedings of the Twenty-Ninth International Joint Conference on Artificial …, 2020 | 5 | 2020 |
| User clustering and scheduling in UAV systems exploiting channel correlation Z Cheng, J Yang, Z Wei, H Yang 2019 IEEE 30th Annual International Symposium on Personal, Indoor and Mobile …, 2019 | 5 | 2019 |
| Automatic modulation recognition of digital signal based on auto-encoding network in MIMO System M Wei, Z Wei, J Yang, L Sang 2018 IEEE 18th international conference on communication technology (ICCT …, 2018 | 5 | 2018 |
| Making AI less “thirsty”: uncovering and addressing the secret water footprint of AI models. arXiv. 2023 P Li, J Yang, MA Islam, S Ren URL http://arxiv. org/abs/2304.03271 98, 0 | 5 | |
| Improving QoE of deep neural network inference on edge devices: A bandit approach B Lu, J Yang, J Xu, S Ren IEEE Internet of Things Journal 9 (21), 21409-21420, 2022 | 4 | 2022 |
| Learning for robust combinatorial optimization: Algorithm and application Z Shao, J Yang, C Shen, S Ren IEEE INFOCOM 2022-IEEE Conference on Computer Communications, 930-939, 2022 | 4 | 2022 |
| A quantitative perspective on values of domain knowledge for machine learning J Yang, S Ren arXiv preprint arXiv:2011.08450, 2020 | 4 | 2020 |
| Poster: Scaling up deep neural network optimization for edge inference B Lu, J Yang, S Ren 2020 IEEE/ACM Symposium on Edge Computing (SEC), 170-172, 2020 | 4 | 2020 |
| Robustified learning for online optimization with memory costs P Li, J Yang, S Ren IEEE INFOCOM 2023-IEEE Conference on Computer Communications, 1-10, 2023 | 3 | 2023 |
