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Virginia Smith

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Everybody Prune Now: Structured Pruning of LLMs with only Forward Passes

Feb 09, 2024
Lucio Dery, Steven Kolawole, Jean-François Kagy, Virginia Smith, Graham Neubig, Ameet Talwalkar

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Leveraging Public Representations for Private Transfer Learning

Jan 16, 2024
Pratiksha Thaker, Amrith Setlur, Zhiwei Steven Wu, Virginia Smith

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Complementary Benefits of Contrastive Learning and Self-Training Under Distribution Shift

Dec 06, 2023
Saurabh Garg, Amrith Setlur, Zachary Chase Lipton, Sivaraman Balakrishnan, Virginia Smith, Aditi Raghunathan

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Noise-Reuse in Online Evolution Strategies

Apr 21, 2023
Oscar Li, James Harrison, Jascha Sohl-Dickstein, Virginia Smith, Luke Metz

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Progressive Knowledge Distillation: Building Ensembles for Efficient Inference

Feb 20, 2023
Don Kurian Dennis, Abhishek Shetty, Anish Sevekari, Kazuhito Koishida, Virginia Smith

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Federated Learning as a Network Effects Game

Feb 16, 2023
Shengyuan Hu, Dung Daniel Ngo, Shuran Zheng, Virginia Smith, Zhiwei Steven Wu

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Bitrate-Constrained DRO: Beyond Worst Case Robustness To Unknown Group Shifts

Feb 06, 2023
Amrith Setlur, Don Dennis, Benjamin Eysenbach, Aditi Raghunathan, Chelsea Finn, Virginia Smith, Sergey Levine

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On Noisy Evaluation in Federated Hyperparameter Tuning

Jan 05, 2023
Kevin Kuo, Pratiksha Thaker, Mikhail Khodak, John Nguyen, Daniel Jiang, Ameet Talwalkar, Virginia Smith

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