| Incorporating compatible pairs in kidney exchange: A dynamic weighted matching model Z Li, K Lieberman, W Macke, S Carrillo, CJ Ho, J Wellen, S Das Proceedings of the 2019 ACM Conference on Economics and Computation, 349-367, 2019 | 19 | 2019 |
| Decoding Compressed Trust: Scrutinizing the Trustworthiness of Efficient LLMs Under Compression J Hong, J Duan, C Zhang, Z Li, C Xie, K Lieberman, J Diffenderfer, ... arXiv preprint arXiv:2403.15447, 2024 | 11 | 2024 |
| Neural Image Compression: Generalization, Robustness, and Spectral Biases K Lieberman, J Diffenderfer, C Godfrey, B Kailkhura Advances in Neural Information Processing Systems (NeurIPS), 2023 | 3 | 2023 |
| Optimizing for ROC Curves on Class-Imbalanced Data by Training over a Family of Loss Functions K Lieberman, S Yuan, SK Ravindran, C Tomasi ICLR 2024 Workshop on Bridging the Gap Between Practice and Theory in Deep …, 2024 | 1 | 2024 |
| Training Over a Distribution of Hyperparameters for Enhanced Performance and Adaptability on Imbalanced Classification K Lieberman, SK Ravindran, S Yuan, C Tomasi arXiv preprint arXiv:2410.03588, 2024 | | 2024 |
| A Multi-Level Machine Learning Approach to the Management of American Chestnut Populations M Allen, Q Goehrig, T Timm, J Wolfe, K Lieberman, R Rouleau, A Baines, ... | | 2018 |
| A Stochastic Epidemiological Model of the Response of American Chestnut Populations to Fungal Blight K Lieberman, R Rouleau, A Davelos Baines, M Allen | | 2017 |
