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Recommendation of data-free class-incremental learning algorithms by simulating future data
Our method outperforms competitive baselines, and performance is close to that of an oracle choosing the best algorithm in each setting.
An Analysis of Initial Training Strategies for Exemplar-Free Class-Incremental Learning
Our main finding is that the initial training strategy is the dominant factor influencing the average incremental accuracy, but that the choice of CIL algorithm is more important in preventing forgetting.
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