WebInspired by the symmetric KL-divergence, we propose the approach of \textbf {Symmetric cross entropy Learning} (SL), boosting CE symmetrically with a noise robust counterpart Reverse Cross Entropy (RCE). Our proposed SL approach simultaneously addresses both the under learning and overfitting problem of CE in the presence of noisy labels. Web1ONE ... 1ONE
Comparison results on the Clothing1M dataset [60]. Download ...
WebApr 28, 2024 · Download a PDF of the paper titled Boosting Co-teaching with … WebApr 28, 2024 · Download PDF Abstract: In this paper, we study the problem of learning image classification models in the presence of label noise. We revisit a simple compression regularization named Nested Dropout. We find that Nested Dropout, though originally proposed to perform fast information retrieval and adaptive data compression, can … china\u0027s poverty-relief stories
Symmetric Cross Entropy for Robust Learning with Noisy Labels
WebDownload scientific diagram Sample images from the Clothing1M dataset. Here, all three images are tagged with “Hoodie” but they include a sweater, skirt or jacket. The images may also ... WebApr 2, 2024 · Experiments on CIFAR-10, CIFAR-100 and Clothing1M demonstrate that this method is the same or superior to the state-of-the-art methods. Download to read the full article text Working on a manuscript? Avoid the common mistakes References. Yan Y, Rosales R, Fung G, Subramanian R, Dy J. Learning from multiple annotators with … WebMar 20, 2024 · Download a PDF of the paper titled PASS: Peer-Agreement based Sample Selection for training with Noisy Labels, by Arpit Garg and 4 other authors. ... Red Mini-Imagenet, Clothing1M, Mini-Webvision, and Imagenet. Our results demonstrate that our new sample selection approach improves the existing SOTA results of algorithms. ... china\u0027s power cuts widen amid