Research map / Architectures and efficiency / Quantization
Explicit Loss-Error-Aware Quantization for Low-Bit Deep Neural Networks
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use explicit loss-error-aware quantization instead of quantization based only on weight reconstruction error | DNN weight quantization · ImageNet | classification accuracy | Helped |
| Use loss-error-aware quantization | DNN quantization · CIFAR-10 | classification accuracy | Helped |
| Use the proposed quantization approach rather than uniform quantization | DNN quantization · ImageNet | classification accuracy | Helped |
Closest papers by meaning
- Adaptive Loss-Aware Quantization for Multi-Bit Networks (CVPR 2020 · similarity 0.92)
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- One-Step Forward and Backtrack: Overcoming Zig-Zagging in Loss-Aware Quantization Training (AAAI 2024 · similarity 0.89)
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