| Improving the energy efficiency of relational and NoSQL databases via query optimizations D Mahajan, C Blakeney, Z Zong Sustainable Computing: Informatics and Systems 22, 120-133, 2019 | 52 | 2019 |
| Parallel blockwise knowledge distillation for deep neural network compression C Blakeney, X Li, Y Yan, Z Zong IEEE Transactions on Parallel and Distributed Systems 32 (7), 1765-1776, 2020 | 40 | 2020 |
| Simon Says: Evaluating and Mitigating Bias in Pruned Neural Networks with Knowledge Distillation C Blakeney, N Huish, Y Yan, Z Zong arXiv preprint arXiv:2106.07849, 2021 | 22 | 2021 |
| Lora learns less and forgets less D Biderman, JG Ortiz, J Portes, M Paul, P Greengard, C Jennings, D King, ... arXiv preprint arXiv:2405.09673, 2024 | 19 | 2024 |
| Is Pruning Compression?: Investigating Pruning Via Network Layer Similarity C Blakeney, Y Yan, Z Zong The IEEE Winter Conference on Applications of Computer Vision, 914-922, 2020 | 15 | 2020 |
| Reduce, Reuse, Recycle: Improving Training Efficiency with Distillation C Blakeney, JZ Forde, J Frankle, Z Zong, ML Leavitt arXiv preprint arXiv:2211.00683, 2022 | 4 | 2022 |
| Craft Distillation: Layer-wise Convolutional Neural Network Distillation C Blakeney, X Li, Y Yan, Z Zong 2020 7th IEEE International Conference on Cyber Security and Cloud Computing …, 2020 | 4 | 2020 |
| Measuring Bias and Fairness in Multiclass Classification C Blakeney, G Atkinson, N Huish, Y Yan, V Metsis, Z Zong 2022 IEEE International Conference on Networking, Architecture and Storage …, 2022 | 3 | 2022 |
| Measure Twice, Cut Once: Quantifying Bias and Fairness in Deep Neural Networks C Blakeney, G Atkinson, N Huish, Y Yan, V Metris, Z Zong arXiv preprint arXiv:2110.04397, 2021 | 3 | 2021 |
| Does your data spark joy? Performance gains from domain upsampling at the end of training C Blakeney, M Paul, BW Larsen, S Owen, J Frankle arXiv preprint arXiv:2406.03476, 2024 | 2 | 2024 |
| Implementing a visual programming editor for VPython C Blakeney, M Dube, H Close, A Roundtree Bulletin of the American Physical Society 62, 2017 | 2 | 2017 |
| Group formation on physics exams SF Wolf, C Blakeney, HG Close Physics education research conference 2016. PER conference, Sacramento, CA …, 2016 | 2 | 2016 |
| Perplexed by Perplexity: Perplexity-Based Data Pruning With Small Reference Models Z Ankner, C Blakeney, K Sreenivasan, M Marion, ML Leavitt, M Paul arXiv preprint arXiv:2405.20541, 2024 | | 2024 |
| Reducing Training Cost and Improving Inference Speed Through Neural Network Compression C Blakeney Texas State University-San Marcos, 2023 | | 2023 |
| Transfer Learning with Fine-grained Sparse Networks: From an Efficient Network Perspective X Li, C Blakeney, Z Zong The Resource-Constrained Machine Learning Workshop in conjunction with IEEE …, 2020 | | 2020 |
| Development and Initial Deployment of a Graphic Editor for GlowScript VPython H Close, C Blakeney, M Dube, E Hauser, B Marks Bulletin of the American Physical Society 62, 2017 | | 2017 |
| Developing a visual programming editor for VPython C Blakeney, M Dube, H Close Bulletin of the American Physical Society 61, 2016 | | 2016 |
| Perplexed by Perplexity: Perplexity-Based Pruning with Small Reference Models Z Ankner, C Blakeney, K Sreenivasan, M Marion, ML Leavitt, M Paul ICLR 2024 Workshop on Mathematical and Empirical Understanding of Foundation …, 0 | | |
Ziliang ZongProfessor of Computer Science, Texas State University在 txstate.edu 的电子邮件经过验证
