13 Matching Annotations
  1. Last 7 days
    1. In other words, programs that send messages to other machines (or to other programs on the same machine) should conform completely to the specifications, but programs that receive messages should accept non-conformant input as long as the meaning is clear.
    2. be conservative in what you do, be liberal in what you accept from others
  2. Oct 2020
  3. Sep 2020
  4. Aug 2020
    1. Ray, E. L., Wattanachit, N., Niemi, J., Kanji, A. H., House, K., Cramer, E. Y., Bracher, J., Zheng, A., Yamana, T. K., Xiong, X., Woody, S., Wang, Y., Wang, L., Walraven, R. L., Tomar, V., Sherratt, K., Sheldon, D., Reiner, R. C., Prakash, B. A., … Consortium, C.-19 F. H. (2020). Ensemble Forecasts of Coronavirus Disease 2019 (COVID-19) in the U.S. MedRxiv, 2020.08.19.20177493. https://doi.org/10.1101/2020.08.19.20177493

  5. Jun 2020
  6. Feb 2019
    1. Are All Layers Created Equal?

      Google的这文2个 idea 很简单:一个是在 trained 网络各层的参数分别换回训练前的初始参数而观察相应各层的鲁棒性;另一个是把上一个 idea 基础上把那套初始参数再从某分布中随机取一次瞅效果。此 paper 的严谨的验证试验过程是最值得学习的~[并不简单]

    2. Using Pre-Training Can Improve Model Robustness and Uncertainty

      此 paper 回应并补充了去年何神的一篇说 pre-training 对 performance 鸟用不大的文章 (Rethinking ImageNet Pre-training)。你问是怎么回应的?瞅一眼此 paper 的题目就晓得了。。。。

  7. Nov 2018
    1. Is Robustness the Cost of Accuracy? -- A Comprehensive Study on the Robustness of 18 Deep Image Classification Models

      这文帅了~ 信息丰富 超多的图~ 让人眼前一亮~

      探讨了18个模型的鲁棒性和准确率。结论很多,如模型构架是影响鲁棒性和准确率的重要因素(似乎是废话);相似模型构架基础上增加“深度”对鲁棒性的提升很微弱;有些模型(Vgg类)的表现出很强的对抗样本迁移性。。。