Learning Non-Parametric Surrogate Losses With Correlated Gradients
Training models by minimizing surrogate loss functions with gradient-based algorithms is a standard approach in various vision tasks. This strategy often leads to suboptimal solutions due to the gap between the target evaluation metrics and surrogate loss functions. In this paper, we propose a frame...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2021-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9570322/ |