Towards Discriminability and Diversity: Batch Nuclear-norm Maximization under Label Insufficient Sit
Abstract 论文做者提出：web In some label insufficient situations, the performance degrades on the decision boundary with high data density. Acommon solution is to directly minimize the Shannon Entropy, but t
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相关文章
- 1. Towards Discriminability and Diversity: Batch Nuclear-norm Maximization under Label Insufficient Sit
- 2. CVPR 2020(Oral) | 中科院等提出BNM：标签不充分下的判别性与多样性约束方法
- 3. Evolutionary approaches towards AI: past, present, and future
- 4. Clustering：Gaussian Mixture Model and Expectation Maximization
- 5. CVPR/AAAI/ECCV顶会论文/代码
- 6. CF677C Vanya and Label
- 7. tf.keras入门(4) Explore over-fitting and under-fitting
- 8. Covariate shift and batch normalization
- 9. DIM（Learning deep representations by mutual information estimation and maximization）
- 10. Batch Training