Normalized total loss on the Facebook dataset (DCOR with and without RLC).
<p>To enable a fair visual comparison of training dynamics, each curve is normalized as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0335135#pone.0335135.e243" target="_blank">Eq (29)</a> by dividing by its epoch-1 value and EMA-smoot...
সংরক্ষণ করুন:
| প্রধান লেখক: | |
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| অন্যান্য লেখক: | , , |
| প্রকাশিত: |
2025
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| বিষয়গুলি: | |
| ট্যাগগুলো: |
ট্যাগ যুক্ত করুন
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| সংক্ষিপ্ত: | <p>To enable a fair visual comparison of training dynamics, each curve is normalized as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0335135#pone.0335135.e243" target="_blank">Eq (29)</a> by dividing by its epoch-1 value and EMA-smoothed (exponential moving average) with . The EMA is computed as with . This normalization emphasizes relative convergence behavior (shape and stability) rather than raw magnitudes: with RLC, the total objective continues to decrease in late epochs, whereas without RLC it plateaus, consistent with the ablation trends in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0335135#pone.0335135.t005" target="_blank">Table 5</a>.</p> |
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