Questions tagged [few-shot-learning]

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Attention module (CBAM) in CNN tend to saturate values to 1

In the context of image classification, I am using a feature extractor based on a resnet-like architecture (ResNet12): four residual blocks, each of which is made of two consecutive conv3x3, batch ...
Lorenzo's user avatar
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Sampling triplet sets in the field of few-shot learning

I have recently been exposed to the concept of K-way N-shot classification. As far as I realize few-shot learning involves meta training and meta testing sets for training and testing our model, ...
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What is the difference betwen fine runing and rlhf for llm?

I am confused about the difference betwen fine runing and rlhf for llm. When to use what? I know RLHF need to creating a reward model which at furst rates responses to align the responses to the ...
Exploring's user avatar
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how to approach this problem (open set classification of diverse folder of images)

suppose we are presented with a folder of images. the task is just detect if any new image should belong in this folder or not. in this folder, there may be natural groups of images that are similar ...
new coding's user avatar
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Using GANs to generate data augmentations for YOLOv5

I was building a YOLOv5 object detection model, and was looking into researching synthetic methods like GANs to increase the size of my training set in an unsupervised manner. I know that few-shot ...
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What is the difference between prompt tuning and prefix tuning?

I read prompt tuning and prefix tuning are two effective mechanisms to leverage frozen language models to perform downstream tasks. What is the difference between the two and how they work really? ...
Exploring's user avatar
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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, ...
Exploring's user avatar
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2 votes
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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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1 answer
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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 ...
Geneveve08's user avatar
4 votes
2 answers
934 views

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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