srch

Here, we propose an LSTM- based meta-learner model to learn the exact optimization algorithm used to train another learner neural network classifier in the ...

需要先了解下LSTM的同学可以先移步此博客，个人觉得讲的很好：. 1. 问题设置（Meta-Learning Problem Set-Up）： 在一般的机器学习问题中，我们在数据集 中训练模型参数，在 中测试模型性能。. 在Meta-Learning问题设置下，我们处理的是Meta-sets ，对其中每一个数据集 ...

pytorch implementation of Optimization as a Model for Few-shot Learning.

LSTM-based meta-learner is to learn the exact optimization algorithm used to train another learner neural network classifier ...

The LSTM meta-learner is a kind of meta-learning. It has two stages: ... The main idea of the LSTM meta-learner is to train an LSTM cell. That is ...

02.11.2021 · And, to run LSTM meta-learner for 5-shot task: th train/run-train.lua --task config.5-shot-5-class --data config.imagenet --model config.lstm.train-imagenet-5shot Contact. For questions about miniImagenet format, please contact …

This repo contains the source code accompanying a scientific paper with the same name. - GitHub - twitter-research/meta-learning-lstm: This repo contains ...

Meta-learning, also known as “learning to learn”, intends to design models that can learn new skills or adapt to new environments ...

Contribute to xiaoshingshing/meta-learning-lstm development by creating an account on GitHub.

Meta-learning can be used to learn a good prior that facilitates quick learning, thereby relaxing these requirements so that new tasks can be ...

Memory augmented neural network (MANN). ○. LSTM meta learner. ○ Model independent approaches. – Optimization based. ○. Model Agnostic Meta-learning (MAML).