Hands-On Meta Learning with Python

Gradient agreement as an optimization

The gradient agreement algorithm is an interesting and recently introduced algorithm that acts as an enhancement to meta learning algorithms. In MAML and Reptile, we try to find a better model parameter that's generalizable across several related tasks so that we can learn quickly with fewer data points. If we recollect what we've learned in the previous chapters, we've seen that we randomly initialize the model parameter and then we sample a random batch of tasks, from the task distribution, . For each ...