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Don't Decay the Learning Rate, Increase the Batch Size

, , and . (2017)cite arxiv:1711.00489Comment: 11 pages, 7 figures.

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Don't decay the learning rate, increase the batch size, , , and . arXiv preprint arXiv:1711.00489, (2017)The (Un)reliability of Saliency Methods., , , , , , , and . Explainable AI, volume 11700 of Lecture Notes in Computer Science, Springer, (2019)Neural Predictor for Neural Architecture Search., , , , , and . CoRR, (2019)Phenaki: Variable Length Video Generation from Open Domain Textual Descriptions., , , , , , , , and . ICLR, OpenReview.net, (2023)Can Weight Sharing Outperform Random Architecture Search? An Investigation With TuNAS., , , , , , and . CVPR, page 14311-14320. Computer Vision Foundation / IEEE, (2020)Discovering Multi-Hardware Mobile Models via Architecture Search., , , , , , , , , and . CVPR Workshops, page 3022-3031. Computer Vision Foundation / IEEE, (2021)The (Un)reliability of saliency methods., , , , , , , and . CoRR, (2017)Backprop Evolution., , , , , and . CoRR, (2018)Dynamic Stopping Improves the Speed and Accuracy of a P300 Speller., , , and . ICANN (1), volume 7552 of Lecture Notes in Computer Science, page 661-668. Springer, (2012)Learning how to explain neural networks: PatternNet and PatternAttribution., , , , , , and . ICLR (Poster), OpenReview.net, (2018)