Comments (2)
kjunelee
commented on June 15, 2024
Sorry for the late reply. At the moment, I don't have a GPU server to run experiments on miniImageNet. Let me get back to this in few days.
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kjunelee
commented on June 15, 2024
Thanks for your interest in our work!
As mentioned in #8, each meta-training run can result in slightly different result. It seems like the result of both ProtoNet and MetaOptNet can vary across different environments. I experienced similar issues with many other few-shot learning algorithms.
The message of our paper is about the gap between non-parametric base learners and parametric base learners, and I believe that the gap should exist within the same environment.
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Related Issues (20)
- Some questions about MetaOptNetHead_Ridge HOT 2
- About accuracy in CIFAR_FS 5-way 5-shot and how to implement MetaOptNet-SVM-trainval HOT 2
- Keep-rate scheduling of DropBlock in a multi-GPU environment HOT 2
- Why the accuracy of the Prototypical Network is higher than the reported version in paper? HOT 1
- Where is the parameter gamma HOT 1
- Does the performance of different SVM heads vary largely? HOT 1
- question about "--episodes-per-batch" HOT 2
- Meta gradient Computation HOT 3
- About"TypeError: btrisolve() takes 3 positional arguments but 4 were given"
- what is the difference between novel categories and base category? HOT 1
- Question about meta-validation and meta-testing HOT 4
- Protonet re-implementation details HOT 3
- Parameters for ProtoNet using ResNet12 as backbone
- the parameters config for the cifarfs,the accuracy is only 63% HOT 1
- could you tell me the link which about the miniImageNet_category_split_train_phase_train.pickle ?
- Thanks and some questions
- Overlapping between meta-training classes and meta-testing classes HOT 1
- How do I know what the real category of tieredImagenet is? HOT 1
- Pretrained model
- Project dependencies may have API risk issues
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