| Federated learning with non-iid data Y Zhao, M Li, L Lai, N Suda, D Civin, V Chandra arXiv preprint arXiv:1806.00582, 2018 | 3267 | 2018 |
| Bit fusion: Bit-level dynamically composable architecture for accelerating deep neural network H Sharma, J Park, N Suda, L Lai, B Chau, JK Kim, V Chandra, ... 2018 ACM/IEEE 45th Annual International Symposium on Computer Architecture …, 2018 | 666 | 2018 |
| Hello edge: Keyword spotting on microcontrollers Y Zhang, N Suda, L Lai, V Chandra arXiv preprint arXiv:1711.07128, 2017 | 568 | 2017 |
| Cmsis-nn: Efficient neural network kernels for arm cortex-m cpus L Lai, N Suda, V Chandra arXiv preprint arXiv:1801.06601, 2018 | 504 | 2018 |
| Multi-scale high-resolution vision transformer for semantic segmentation J Gu, H Kwon, D Wang, W Ye, M Li, YH Chen, L Lai, V Chandra, DZ Pan Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 261 | 2022 |
| Heterogeneous dataflow accelerators for multi-DNN workloads H Kwon, L Lai, M Pellauer, T Krishna, YH Chen, V Chandra 2021 IEEE International Symposium on High-Performance Computer Architecture …, 2021 | 160 | 2021 |
| Co-exploration of neural architectures and heterogeneous asic accelerator designs targeting multiple tasks L Yang, Z Yan, M Li, H Kwon, L Lai, T Krishna, V Chandra, W Jiang, Y Shi 2020 57th ACM/IEEE design automation conference (DAC), 1-6, 2020 | 151 | 2020 |
| Deep convolutional neural network inference with floating-point weights and fixed-point activations L Lai, N Suda, V Chandra arXiv preprint arXiv:1703.03073, 2017 | 139 | 2017 |
| Federated learning with non-IID data (2018) Y Zhao, M Li, L Lai, N Suda, D Civin, V Chandra arXiv preprint arXiv:1806.00582, 1806 | 100 | 1806 |
| Federated learning with non-iid data. arXiv 2018 Y Zhao, M Li, L Lai, N Suda, D Civin, V Chandra arXiv preprint arXiv:1806.00582, 2018 | 99 | 2018 |
| Federated learning with non-iid data. arXiv Y Zhao, M Li, L Lai, N Suda, D Civin, V Chandra arXiv preprint arXiv:1806.00582 10, 2018 | 94 | 2018 |
| Mobilellm: Optimizing sub-billion parameter language models for on-device use cases Z Liu, C Zhao, F Iandola, C Lai, Y Tian, I Fedorov, Y Xiong, E Chang, ... Forty-first International Conference on Machine Learning, 2024 | 85 | 2024 |
| Enabling deep learning at the lot edge L Lai, N Suda 2018 IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 1-6, 2018 | 70 | 2018 |
| SenseHAR: a robust virtual activity sensor for smartphones and wearables JV Jeyakumar, L Lai, N Suda, M Srivastava Proceedings of the 17th Conference on Embedded Networked Sensor Systems, 15-28, 2019 | 65 | 2019 |
| Device-and circuit-level variability caused by line edge roughness for sub-32-nm FinFET technologies G Leung, L Lai, P Gupta, CO Chui IEEE transactions on electron devices 59 (8), 2057-2063, 2012 | 59 | 2012 |
| SlackProbe: A low overhead in situ on-line timing slack monitoring methodology L Lai, V Chandra, R Aitken, P Gupta 2013 Design, Automation & Test in Europe Conference & Exhibition (DATE), 282-287, 2013 | 58 | 2013 |
| DDRO: A novel performance monitoring methodology based on design-dependent ring oscillators TB Chan, P Gupta, AB Kahng, L Lai Thirteenth International Symposium on Quality Electronic Design (ISQED), 633-640, 2012 | 58 | 2012 |
| Privynet: A flexible framework for privacy-preserving deep neural network training M Li, L Lai, N Suda, V Chandra, DZ Pan arXiv preprint arXiv:1709.06161, 2017 | 55 | 2017 |
| System and method for performing small channel count convolutions in energy-efficient input operand stationary accelerator G Venkatesh, L Lai, I Pierce, J Chuang, M Li US Patent 11,675,998, 2023 | 50 | 2023 |
| SlackProbe: A Flexible and Efficient In Situ Timing Slack Monitoring Methodology L Lai, V Chandra, RC Aitken, P Gupta IEEE Transactions on Computer-Aided Design of Integrated Circuits and …, 2014 | 45 | 2014 |
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