A Universal Growth Rate for Learning with Smooth Surrogate Losses

Nov-17-2025, 03:43:28 GMT–Neural Information Processing Systems

We first examine how H -consistency bounds vary across surrogates based on the number of classes.

artificial intelligence, machine learning, minimizability gap, (17 more...)

Neural Information Processing Systems

Nov-17-2025, 03:43:28 GMT

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Country:
- Asia > Middle East > Jordan (0.04)

Genre:
- Research Report
  - Experimental Study (0.92)
  - New Finding (0.92)

Technology:
- Information Technology > Artificial Intelligence > Machine Learning > Neural Networks (0.93)

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A Universal Growth Rate for Learning with Smooth Surrogate Losses

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