Questions tagged [few-shot-learning]

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Multi Label fine tuning of Zero Shot Classifier [closed]

Need to fine-tune the following Zero Shot Classifier (converting it to Few-Shot?): https://huggingface.co/facebook/bart-large-mnli Looking for resources/tutorials
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Prototypical Network - Should I train my backbone or a separate embedder?

When I read the prototypical paper Prototypical Networks for Few-shot Learning, I understand in Eq. 1 that I should train $f_\phi$, which takes as input $x_i$, which is already an embedding of an ...
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What is the difference between fine tuning and variants of few shot learning? [duplicate]

I am trying to understand the concept of fine-tuning and few-shot learning. I understand the need for fine-tuning. It is essentially tuning a pre-trained model to a specific downstream task. However, ...
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Are tasks created at random for training, validation, and testing of Meta Learning algorithms?

When we feed the data to a Meta Learning algorithm, e.g., Prototypical Network, do we create the dataloader in a way to see each training instance only once a epoch, or is it just random for ease of ...
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Comparing large numbers of images to find outliers

There are many methods you can use to compare two images in ML (Siamese NN, CNNs, Ect.) What I cannot figure out is comparing a large number of images (Without Retraining) to find images of a ...
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In few-shot classification, should I use my custom dataset as the validation dataset and mini-ImageNet as the training dataset?

I am new to few-shot learning, and I wanted to get a hands-on understanding of it, using Reptile algorithm, applied to my custom dataset. My custom dataset has 30 categories, with 5 images per ...
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How is few-shot learning different from transfer learning?

To my understanding, transfer learning helps to incorporate data from other related datasets and achieve the task with less labelled data (maybe in 100s of images per category). Few-shot learning ...
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What are some use cases of few-shot learning?

Besides computer vision and image classification, what other use cases/applications are for few-shot learning?
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