| Bayesian Tensorized Neural Networks with Automatic Rank Selection C Hawkins, Z Zhang Neurocomputing, 2019 | 50 | 2019 |
| Towards compact neural networks via end-to-end training: A Bayesian tensor approach with automatic rank determination C Hawkins, X Liu, Z Zhang SIAM Journal on Mathematics of Data Science 4 (1), 46-71, 2022 | 42 | 2022 |
| Variational Bayesian Inference for Robust Streaming Tensor Factorization and Completion C Hawkins, Z Zhang 2018 IEEE International Conference on Data Mining (ICDM), 1446-1451, 2018 | 35* | 2018 |
| On-FPGA training with ultra memory reduction: A low-precision tensor method K Zhang, C Hawkins, X Zhang, C Hao, Z Zhang arXiv preprint arXiv:2104.03420, 2021 | 15 | 2021 |
| Efficient long-range transformers: You need to attend more, but not necessarily at every layer Q Zhang, D Ram, C Hawkins, S Zha, T Zhao arXiv preprint arXiv:2310.12442, 2023 | 13 | 2023 |
| VCC: scaling transformers to 128k tokens or more by prioritizing important tokens Z Zeng, C Hawkins, M Hong, A Zhang, N Pappas, V Singh, S Zheng Advances in Neural Information Processing Systems 36, 20260-20286, 2023 | 9 | 2023 |
| 3U-EdgeAI: Ultra-low memory training, ultra-low bitwidth quantization, and ultra-low latency acceleration Y Chen, C Hawkins, K Zhang, Z Zhang, C Hao Proceedings of the 2021 Great Lakes Symposium on VLSI, 157-162, 2021 | 9 | 2021 |
| Low-rank+ sparse tensor compression for neural networks C Hawkins, H Yang, M Li, L Lai, V Chandra arXiv preprint arXiv:2111.01697, 2021 | 8 | 2021 |
| Bayesian Tensor Learning with Automatic Rank Determination and Uncertainty Quantification K Zhang, C Hawkins, Z Zhang Frontiers in Artificial Intelligence, 201, 2022 | 7* | 2022 |
| Tensor methods for generating compact uncertainty quantification and deep learning models C Cui, C Hawkins, Z Zhang 2019 IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 1-6, 2019 | 5 | 2019 |
| Online MCMC thinning with kernelized Stein discrepancy A Koppel, J Eappen, S Bhatt, C Hawkins, S Ganesh SIAM Journal on Mathematics of Data Science 6 (1), 51-75, 2024 | 3 | 2024 |
| Online, informative mcmc thinning with kernelized stein discrepancy C Hawkins, A Koppel, Z Zhang arXiv preprint arXiv:2201.07130, 2022 | 3 | 2022 |
| Scalable consistency training for graph neural networks via self-ensemble self-distillation C Hawkins, VN Ioannidis, S Adeshina, G Karypis arXiv preprint arXiv:2110.06290, 2021 | 3 | 2021 |
| Rational combinations of Betti diagrams of complete intersections MT Annunziata, CR Gibbons, C Hawkins, AJ Sutherland Journal of Algebra and Its Applications 17 (05), 1850079, 2018 | 3 | 2018 |
| Generating prompt recommendations for natural language processing tasks S Zha, MB Martinez, Y Benajiba, C Hawkins, A Rawal, D Ram, MRS Tan, ... US Patent App. 18/067,680, 2024 | 1 | 2024 |
| Sequence-level Large Language Model Training with Contrastive Preference Optimization Z Feng, D Ram, C Hawkins, A Rawal, J Zhao, S Zha arXiv preprint arXiv:2502.16433, 2025 | | 2025 |
| Adapting prompts selected from prompt task collections S Zha, MB Martinez, Y Benajiba, C Hawkins, A Rawal, D Ram, MRS Tan, ... US Patent App. 18/067,674, 2024 | | 2024 |
| Compressed Training for Uncertainty-Aware Compact Neural Networks CP Hawkins University of California, Santa Barbara, 2022 | | 2022 |
Zheng ZhangAssociate Professor of ECE, UCSBVerified email at ece.ucsb.edu