Virginia Smith
Carnegie Mellon University
H-index: 28
North America-United States
Top articles of Virginia Smith
Title | Journal | Author(s) | Publication Date |
|---|---|---|---|
Progressive Ensemble Distillation: Building Ensembles for Efficient Inference | Advances in Neural Information Processing Systems | Don Dennis Abhishek Shetty Anish Prasad Sevekari Kazuhito Koishida Virginia Smith | 2023/12 |
Privacy Amplification for the Gaussian Mechanism via Bounded Support | arXiv preprint arXiv:2403.05598 | Shengyuan Hu Saeed Mahloujifar Virginia Smith Kamalika Chaudhuri Chuan Guo | 2024/3/7 |
Complementary Benefits of Contrastive Learning and Self-Training Under Distribution Shift | Advances in Neural Information Processing Systems | Saurabh Garg Amrith Setlur Zachary Lipton Sivaraman Balakrishnan Virginia Smith | 2024/2/13 |
Many-Objective Multi-Solution Transport | arXiv preprint arXiv:2403.04099 | Ziyue Li Tian Li Virginia Smith Jeff Bilmes Tianyi Zhou | 2024/3/6 |
Everybody Prune Now: Structured Pruning of LLMs with only Forward Passes | arXiv preprint arXiv:2402.05406 | Lucio Dery Steven Kolawole Jean-Francois Kagey Virginia Smith Graham Neubig | 2024/2/8 |
Guardrail baselines for unlearning in llms | arXiv preprint arXiv:2403.03329 | Pratiksha Thaker Yash Maurya Virginia Smith | 2024/3/5 |
Attacking LLM Watermarks by Exploiting Their Strengths | arXiv preprint arXiv:2402.16187 | Qi Pang Shengyuan Hu Wenting Zheng Virginia Smith | 2024/2/25 |
Federated Learning as a Network Effects Game | arXiv preprint arXiv:2302.08533 | Shengyuan Hu Dung Daniel Ngo Shuran Zheng Virginia Smith Zhiwei Steven Wu | 2023/2/16 |
Multi-Objective Multi-Solution Transport | Ziyue Li Tian Li Virginia Smith Jeff Bilmes Tianyi Zhou | 2023/10/13 | |
Bitrate-constrained DRO: Beyond worst case robustness to unknown group shifts | arXiv preprint arXiv:2302.02931 | Amrith Setlur Don Dennis Benjamin Eysenbach Aditi Raghunathan Chelsea Finn | 2023/2/6 |
Progressive Knowledge Distillation: Balancing Inference Latency and Accuracy at Runtime | Don Dennis Abhishek Shetty Anish Sevekari Kazuhito Koishida Virginia Smith | 2023/7/16 | |
Progressive Knowledge Distillation: Building Ensembles for Efficient Inference | arXiv e-prints | Don Kurian Dennis Abhishek Shetty Anish Sevekari Kazuhito Koishida Virginia Smith | 2023/2 |
Noise-reuse in online evolution strategies | arXiv preprint arXiv:2304.12180 | Oscar Li James Harrison Jascha Sohl-Dickstein Virginia Smith Luke Metz | 2023/4/21 |
On tilted losses in machine learning: Theory and applications | Journal of Machine Learning Research | Tian Li Ahmad Beirami Maziar Sanjabi Virginia Smith | 2023 |
On noisy evaluation in federated hyperparameter tuning | Proceedings of Machine Learning and Systems | Kevin Kuo Pratiksha Thaker Mikhail Khodak John Nguyen Daniel Jiang | 2023/3/18 |
Leveraging public representations for private transfer learning | arXiv preprint arXiv:2312.15551 | Pratiksha Thaker Amrith Setlur Zhiwei Steven Wu Virginia Smith | 2023/12/24 |
Validating large language models with relm | Proceedings of Machine Learning and Systems | Michael Kuchnik Virginia Smith George Amvrosiadis | 2023/3/18 |
Variance-Reduced Gradient Estimation via Noise-Reuse in Online Evolution Strategies | Oscar Li James Harrison Jascha Sohl-Dickstein Virginia Smith Luke Metz | 2023/11/2 | |
Maximizing entropy on adversarial examples can improve generalization | Amrith Setlur Benjamin Eysenbach Virginia Smith Sergey Levine | 2022/3/25 | |
Private adaptive optimization with side information | Tian Li Manzil Zaheer Sashank Reddi Virginia Smith | 2022/6/28 |
Co-Authors
