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New algorithm efficiently learns ReLUs using queries

By PulseAugur Editorial · [2 sources] ·

Researchers have developed a new computationally efficient algorithm for learning general ReLUs in an interactive setting. This algorithm significantly reduces the number of required label queries compared to passive learning methods. The study also establishes that query access is crucial for improving label complexity in active learning scenarios. AI

IMPACT Introduces a more efficient method for learning complex neural network components, potentially speeding up model development.

RANK_REASON The cluster contains an academic paper detailing a new algorithm for a machine learning task.

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

COVERAGE [2]

  1. arXiv cs.LG TIER_1 English(EN) · Ilias Diakonikolas, Daniel M. Kane, Mingchen Ma ·

    Robust Regression of General ReLUs with Queries

    arXiv:2606.11130v1 Announce Type: new Abstract: We study the task of agnostically learning general (as opposed to homogeneous) ReLUs under the Gaussian distribution with respect to the squared loss. In the passive learning setting, recent work gave a computationally efficient alg…

  2. arXiv cs.LG TIER_1 English(EN) · Mingchen Ma ·

    Robust Regression of General ReLUs with Queries

    We study the task of agnostically learning general (as opposed to homogeneous) ReLUs under the Gaussian distribution with respect to the squared loss. In the passive learning setting, recent work gave a computationally efficient algorithm that uses $poly(d,1/ε)$ labeled examples …

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