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In the implementation details section of your paper, A.1 you mentioned that you use the same general experiment structure for Fixmatch and other competing methods. Where can I find the relevant sectio…
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I wonder the reason for the large gaps between the error rates of the original paper (FixMatch) and this implementation.
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发现train_fixmatch_standard_augs.py文件存在一个有趣的问题：
如果通过命令行指令修改--conf_thresh 的值，会报错没有这个参数
我在尝试寻找问题时将该参数…
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I try to apply FixMatch on one class data.
For the unsupervised loss part, I modified the code like that.
```
self.uce_loss = torch.nn.BCEWithLogitsLoss(reduction='none')
with torch.no_grad():
…
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Thanks for your work.
I am a beginner, so I'm quite puzzled by the following issue.
I trained models using three different algorithms: fixmatch, comatch, and fixmatch_ccssl, following the programs…
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哥们你论文写的乱的，我以为我自己智商除了b问题，你是碰到熟人了吧给你中了
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Thanks for your work. I've tried to modify the current config files of fixmatch-ccssl on CIFAR100 and failed to reproduce the same reuslts on CIFAR10 as your paper shows. Would you publish the related…
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Thanks for your great work!
I met some problems when I reimplemented the Fixmatch results in your table. The error rate of Fixmatch is 7.4% on CIFAR10(Known/Unknown 6/4, number of the labeled image…
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## 一言でいうと
半教師あり手法で、弱Augmentationのデータに対し予測の確信度が高いものを学習データとして採用し、今度は強Augmentationをかけた上で予測結果が変わらないよう学習する。シンプルな手法ながら、CIFAR-10において250ラベルのみで94.93%を達成。
![image](https://user-images.githubusercontent.co…