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New optimization framework generalizes concavity and DR-submodularity

By PulseAugur Editorial · [1 sources] ·

This paper introduces a new framework called upper-linearizable/quadratizable functions, which generalizes concepts like concavity and DR-submodularity. The authors developed a meta-algorithm that can convert existing algorithms for linear or quadratic maximization into ones capable of optimizing these new function types. This approach offers a unified method for solving DR-submodular optimization problems and extends to various feedback settings, improving state-of-the-art results and achieving dynamic and adaptive regret guarantees. AI

RANK_REASON The cluster contains an academic paper detailing a novel mathematical framework and algorithms for optimization problems. [lever_c_demoted from research: ic=1 ai=0.4]

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New optimization framework generalizes concavity and DR-submodularity

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The cluster contains an academic paper detailing a novel mathematical framework and algorithms for optimization problems. [lever_c_demoted from research: ic=1 ai=0.4]
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COVERAGE [1]

  1. arXiv cs.LG TIER_1 English(EN) · Mohammad Pedramfar, Vaneet Aggarwal ·

    From Linear to Linearizable Optimization: A Novel Framework with Applications to Stationary and Non-stationary DR-submodular Optimization

    arXiv:2405.00065v4 Announce Type: replace-cross Abstract: This paper introduces the notion of upper-linearizable/quadratizable functions, a class that extends concavity and DR-submodularity in various settings, including monotone and non-monotone cases. A general meta-algorithm i…

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