few shot learning good articles

https://towardsdatascience.com/advances-in-few-shot-learning-a-guided-tour-36bc10a68b77 great brief summary over matching networks, prototypical networks, model-agnostic meta-learning(MAML). well, the first two topics are well explained but MAML section needs a lot more thinking to understand. Also, I think MAML is closer to the topic of meta-learning rather than few shot learning. https://arxiv.org/pdf/2008.06365.pdf “An Overview of Deep Read more…

paper review: “EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”

arxiv: https://arxiv.org/pdf/1905.11946.pdf key point propose ‘compound scaling method’ which scales all width/depth/resolution together which is an efficient scaling method that can be applied to any existing structure introduce a new family of baseline structure called ‘EfficientNets’. The very smallest baseline structure was found by authors through NAS, and then the Read more…

paper review: “Generative Teaching Networks: Accelerating Neural Architecture Search by Learning to Generate Synthetic Training Data”

https://arxiv.org/abs/1912.07768 This work suggests that surrogate data need not be drawn from the original data distribution.This paper investigates the question of whether we can train a data-generating network that can produce synthetic data that effectively and efficiently teaches a target task to a learner propose new method to create synthetic Read more…