The relative rankings of continual learning methods are not preserved across different fine-tuning regimes defined by trainable parameter depth.
Franco Scarselli, Marco Gori, Ah Tsoi, Markus Hagenbuchner, and Gabriele Monfardini
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Fine-Tuning Regimes Define Distinct Continual Learning Problems
The relative rankings of continual learning methods are not preserved across different fine-tuning regimes defined by trainable parameter depth.