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## Abstract 本文：Myia Github: https://github.com/mila-iqia/myia Task: Review automatic differentiation for array programming in machine learning, propos 阅读全文
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## Abstract 本文: review on adversarial attacks on CV models Task: 1. design of attack 2. defenses 3. evaluate adversarial attacks in real-world scenari 阅读全文
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## Abstract Github: https://github.com/lts4/deepfool 背景：neural networks对小的扰动的表现并不稳定 本文: Deepfool Task: compute perturbations that fool deep networks 阅读全文
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## Abstract 本文: DeepCheck Task: Testing DNNs with lightweight symbolic execution and program analysis Method: use lightweight symbolic analysis to ide 阅读全文
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## Abstract 背景：大多数defenses against adversarial立刻被证明不可用 本文: review on defenses against adversarial attacks Task: 1. method 2. commonly adopted best pra 阅读全文
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## Abstract 本文： Github: 1. https://github.com/MadryLab/mnist_challenge 2. https://github.com/MadryLab/cifar10_challenge Task: 1. study the adversarial 阅读全文
Proj CDeepFuzz Paper Reading: Exposing numerical bugs in deep learning via gradient back-propagation
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## Abstract 背景：numerical bugs可能导致NaN或者Inf这样的异常值，这种异常值被传播后最后会造成如log()这类的函数崩溃 本文：GRIST Github: https://github.com/Jacob-yen/GRIST Task: generate a small 阅读全文
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## Abstract 本文： Task: formalize the space of adversaries against DNNs and then introduce an adversarial testing 实验： 方法：defining a hardness measure 效果： 阅读全文
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## Abstract 背景： the robustness requires the model to produce consistent decisions given minorly perturbed code inputs 本文:CARROT Github: https://github 阅读全文
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## Abstract 阅读全文