ContinualAI RG: “IIRC: Incremental Implicitly-Refined Classification”

Friday 5-03-2021, CET, for the ContinualAI Reading Group, Mohamed Abdelsalam (MILA) presented the paper: Title: “IIRC: Incremental Implicitly-Refined Classification” Abstract: We introduce the “Incremental Implicitly-Refined Classi-fication (IIRC)” setup, an extension to the class incremental learning setup where the incoming batches of classes have two granularity levels. i.e., each sample could have a high-level (coarse) label like “bear” and a low-level (fine) label like “polar bear”. Only one label is provided at a time, and the model has to figure out the other label if it has already learnfed it. This setup is more aligned with real-life scenarios, where a learner usually interacts with the same family of entities multiple times, discovers more granularity about them, while still trying not to forget previous knowledge. Moreover, this setup enables evaluating models for some important lifelong learning challenges that cannot be easily addressed under the existing setups. These chall