【Paper Readind】:Ternary weight networks
Ternary weight networks 2016 NIPS 中科院 Fengfu Li and Bo Zhang 摘要 本文引入了權值爲+1、0和-1的三元神經網絡(TWNs)。最小化全精度(float或者double)的權重與三元權重之間的歐幾里得距離。此外，對基於閾值的三值化函數進行了優化，能夠更快速、且更易於計算地得到近似解。TWNs比最近提出的二值網絡具有更強的表達能力，並且比後者
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相關文章
- 1. Ternary weight networks
- 2. Ternary weight networks論文解讀
- 3. Ternary weight networks 論文筆記
- 4. Ternary Neural Networks with Fine-Grained Quantization
- 5. Paper Notes: Graph Attention Networks
- 6. Paper Reading: Slimmable Neural Networks
- 7. Paper Reading《Relation Networks for Object Detection》
- 8. [paper]ADVERSARIAL REPROGRAMMING OF NEURAL NETWORKS
- 9. 【Paper】TextCNN：Convolutional Neural Networks for Sentence Classification
- 10. 三值網絡--Trained Ternary Quantization