| 2025 | COLT | DiscQuant: A Quantization Method for Neural Networks Inspired by Discrepancy Theory. | Jerry Chee, Arturs Backurs, Rainie Heck, Li Zhang, Janardhan Kulkarni, Thomas Rothvoss, Sivakanth Gopi |
| 2025 | WWW | Datasets for Navigating Sensitive Topics in Recommendation Systems. | Amelia Kovacs, Jerry Chee, Sarah Dean |
| 2024 | ICML | QuIP#: Even Better LLM Quantization with Hadamard Incoherence and Lattice Codebooks. | Albert Tseng, Jerry Chee, Qingyao Sun, Volodymyr Kuleshov, Christopher De Sa |
| 2024 | KDD | Harm Mitigation in Recommender Systems under User Preference Dynamics. | Jerry Chee, Shankar Kalyanaraman, Sindhu Kiranmai Ernala, Udi Weinsberg, Sarah Dean, Stratis Ioannidis |
| 2023 | AISTATS | "Plus/minus the learning rate": Easy and Scalable Statistical Inference with SGD. | Jerry Chee, Hwanwoo Kim, Panos Toulis |
| 2022 | ICLR | How Low Can We Go: Trading Memory for Error in Low-Precision Training. | Chengrun Yang, Ziyang Wu, Jerry Chee, Christopher De Sa, Madeleine Udell |
| 2022 | MMSP | Performance optimizations on U-Net speech enhancement models. | Jerry Chee, Sebastian Braun, Vishak Gopal, Ross Cutler |
| 2018 | AISTATS | Convergence diagnostics for stochastic gradient descent with constant learning rate. | Jerry Chee, Panos Toulis |