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Found 2 papers, 1 papers with code
Parameter-Efficient Transfer Learning for NLP
On GLUE, we attain within 0. 4% of the performance of full fine-tuning, adding only 3. 6% parameters per task.
Ranked #4 on
Image Classification
on OmniBenchmark
(using extra training data)
Statistical Estimation: From Denoising to Sparse Regression and Hidden Cliques
These notes review six lectures given by Prof. Andrea Montanari on the topic of statistical estimation for linear models.
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