N-Shot Learning

N-SHOT LEARNING
1.​Zero shot, one shot, few shot (siamese is one shot)
ZERO SHOT LEARNING
1.​Instead of using class labels, we use some kind of vector representation for the classes, taken from a co-occurrence-after-svd or word2vec. - quite clever. This enables us to figure out if a new unseen class is near one of the known supervised classes. KNN can be used or some other distance-based classifier. Can we use word2vec for similarity measurements of new classes?

Image by Dr. Timothy Hospedales, Yandex​

for classification, we can use nearest neighbour or manifold-based labeling propagation.

Image by Dr. Timothy Hospedales, Yandex
Multiple category vectors? Multilabel zero-shot also in the video
2.​with siamese networks​
GPT3 is ZERO, ONE, FEW
1.​Prompt Engineering Tips & Tricks​
2.​Open GPT3 prompt engineering​

Online Learning

Data Science

Last modified 1yr ago