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papersSEP 10 04:00 UTC

Exact-form regret analysis for gradient descent, mirror descent, and follow-the-regularized-leader

A newly posted arXiv paper investigates how online learning methods such as gradient descent, mirror descent, and follow-the-regularized-leader behave when measured against more demanding, action-dependent benchmarks rather than fixed comparison points. Moving past the standard external regret framing, the authors pursue a geometric account of these deviations and derive closed-form expressions for the resulting regret bounds.

follow-the-regularized-leadergradient descentmirror descentonline learningregret analysisregret bounds

COVERAGE · 1 REPORT · LINKS GO TO THE ORIGINAL OUTLETS

arXiv cs.LGExact-Form Regret for Gradient Descent, Mirror Descent and Follow-the-Regularized-Leader ↗SEP 10 04:00 UTC

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