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3 votes

What are some use cases of few-shot learning?

Few-short learning (FSL) can be useful for many (if not all) machine learning problems, including supervised learning (regression and classification) and reinforcement learning. The paper ...
nbro's user avatar
  • 40.8k
3 votes

What is the difference between fine tuning and variants of few shot learning?

I believe the standard meanings are as follows, but not everyone uses words in the same way, so you might see examples that differ. Fine tuning refers to slightly changing the weights of a pre-trained ...
Lee Reeves's user avatar
2 votes

How is few-shot learning different from transfer learning?

They use the same techniques, but study different problems. Transfer learning always does not imply that the novel classes have very-few samples (as few as 1 per class). Few-shot learning does. The ...
Arjun Ashok's user avatar
2 votes

What is the difference betwen fine runing and rlhf for llm?

RLHF is just one possibility of fine-tuning for generative LLMs, which is used to align an LLM to human tastes. However, you could just create a bunch of great data, and fine-tune (take a pretrained ...
Alberto's user avatar
  • 2,233
1 vote
Accepted

Using GANs to generate data augmentations for YOLOv5

You can use conditional GANs for synthesizing data with labels/bounding boxes. Conditional GANs are GANs where, besides the normal random noise (prior), you also insert additional information which ...
Robin van Hoorn's user avatar

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