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Related Questions
- Can low-rank approximations be applied to convolutional neural networks to reduce memory usage?
- How do low-rank approximations compare to other memory-reduction techniques such as pruning and quantization?
- Can low-rank approximations be used to speed up the training time of neural networks?
- What are the potential trade-offs between accuracy and memory usage when using low-rank approximations in neural networks?
- Have low-rank approximations been successfully applied to recurrent neural networks or transformers?
- Can low-rank approximations be used to reduce the memory requirements of neural networks running on edge devices with limited memory?
- How do low-rank approximations affect the interpretability of neural network models?
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