Towards More Objective Evaluation of Class Incremental Learning: Representation Learning Perspective

no code implementations • 16 Jun 2022 • Sungmin Cha, Jihwan Kwak, Dongsub Shim, Hyunwoo Kim, Moontae Lee, Honglak Lee, Taesup Moon

While the common method for evaluating CIL algorithms is based on average test accuracy for all learned classes, we argue that maximizing accuracy alone does not necessarily lead to effective CIL algorithms.

Class Incremental Learning Incremental Learning +2

SS-IL: Separated Softmax for Incremental Learning

no code implementations • ICCV 2021 • Hongjoon Ahn, Jihwan Kwak, Subin Lim, Hyeonsu Bang, Hyojun Kim, Taesup Moon

To that end, we analyze that computing the softmax probabilities by combining the output scores for all old and new classes could be the main cause of the bias.

Class Incremental Learning Incremental Learning +1