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On Regret Bounds for Continual Single-index Learning by Mai, The Tien is a scholarly article available to read on EtoBox.

What is On Regret Bounds for Continual Single-index Learning about?

In this paper, we generalize the problem of single-index model to the context of continual learning in which a learner is challenged with a sequence of tasks one by one and the dataset of each task is revealed in an online fashion. We propose a randomized strategy that is able to learn a common single-index (meta-parameter) for all tasks and a specific link function for each task. The common single-index allows to transfer the information gained from the previous tasks to a new one. We provide a rigorous theoretical analysis of our proposed strategy by proving some regret bounds under different assumption on the loss function.

Author

Mai, The Tien

Published

2021

Language

EN