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October 3, 2025Open Access

Learning Low-Dimensional Embeddings for Black-Box Optimization

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Authors

RBRiccardo BusettoMMManas MejariMFMarco Forgione

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Overview

Proposed approach reduces effort in black-box optimization for high-dimensional problems, leveraging meta-learning.

Key Points

  • This method enables faster optimization in reduced-dimensional spaces, improving efficiency.
  • By pre-computing a manifold, it lowers the trial budget required for optimization tasks.
  • The approach focuses on a specific class of optimization problems, enhancing predictability.
  • Utilizing meta-learning allows for effective adaptation to new problem instances from the same class.

Cite This Study

Busetto et al. (2025) studied this question.

synapsesocial.com/papers/68e03501f0e39f13e7fa3aafhttps://doi.org/10.48550/arxiv.2505.01112
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