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    Machine learning foundations· 2003

    Online Convex Programming and Generalized Infinitesimal Gradient Ascent

    Martin Zinkevich (first author) · 2003

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    OpenAlex W2148825261

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    Why it matters

    Established online gradient methods with sublinear regret, foundational to modern online optimization.

    Condensed from the expert lists' notes.

    The record

    First released
    2003 (from OpenAlex)
    Citations
    2,914 citations, as counted by Semantic Scholar logoSemantic Scholar (non-commercial licence)
    Named by
    the chatgpt list only
    Score
    0.256 · computed rank 723 · consensus 0.23, must-read 0, citations percentile 0.533 (2000s · foundations), awards 0, existing lists 0. Method

    Data sources

    Catalogue data from OpenAlex (CC0), Crossref (CC0 metadata; no abstracts are shown), arXiv, and Papers With Code (CC BY-SA 4.0), and Semantic Scholar logoSemantic Scholar (used under its non-commercial API licence). Each count names its source. See the method.