FastODT: A tree-based framework for efficient continual learning
arXiv:2603.13276v1 Announce Type: new Abstract: Machine learning models deployed in real-world settings must operate under evolving data distributions and constrained computational resources. This challenge is …
Daniel Bretsko, Piotr Walas, Devashish Khulbe, Sebastian Stros, Stanislav Sobolevsky, Tomas Satura
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