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Sine Activated Low-Rank Matrices for Parameter Efficient Learning

By Yiping Ji and others
Low-rank decomposition has emerged as a vital tool for enhancing parameter efficiency in neural network architectures, gaining traction across diverse applications in machine learning. These techniques significantly lower the number of parameters, striking a balance between compactness and performance. However, a common challenge has been the compromise between parameter efficiency... Show more
March 28, 2024
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