Carl Kingsford

Efficient Heterogeneous Meta-Learning via Channel Shuffling Modulation

We tackle the problem of meta-learning across heterogenous tasks. This problem seeks to extract and generalize transferable meta-knowledge through streaming task sets from a multi-modal task distribution. The extracted meta-knowledge can be used to create predictors for new tasks using a small numbe…