原创 Max-Mahalanobis Linear Discriminant Analysis Networks

文章目錄概主要內容 Pang T, Du C, Zhu J, et al. Max-Mahalanobis Linear Discriminant Analysis Networks[C]. international conf

原创 KKT (LICQ)

文章目錄基本內容LICQ 假設KKT 定理KKT定理的證明引理AFarkas 引理推論KKT定理的證明 H. E. Krogstad, TMA 4180 Optimeringsteori KARUSH-KUHN-TUCKER

原创 Differential Evolution: A Survey of the State-of-the-Art

文章目錄概主要內容DE/rand/1/binDE/?/?/?DE/rand/1/expDE/best/1DE/best/2DE/rand/2超參數的選擇FFF的選擇NPNPNP的選擇CrCrCr的選擇一些連續變體ABCDEG一些缺

原创 Bayesian Optimization with a Finite Budget: An Approximate Dynamic Programming Approach

文章目錄概主要內容 Lam R, Willcox K, Wolpert D H, et al. Bayesian Optimization with a Finite Budget: An Approximate Dynamic

原创 Geometric GAN

文章目錄概主要內容McGAN結合SVM訓練ζ\zetaζ訓練gθg_{\theta}gθ​理論分析證明 Jae Hyun Lim, Jong Chul Ye, Geometric GAN. 概 很有趣, GAN的訓練過程可以分

原创 Distillation as a Defense to Adversarial Perturbations against Deep Neural Networks

文章目錄概主要內容算法一些有趣的指標魯棒性定義合格的抗干擾機制代碼 Nicolas Papernot, Patrick McDaniel, Xi Wu, Somesh Jha, Ananthram Swami, Distilla

原创 EXPLAINING AND HARNESSING ADVERSARIAL EXAMPLES

文章目錄概主要內容從線性談起非線性 Goodfellow I, Shlens J, Szegedy C, et al. Explaining and Harnessing Adversarial Examples[J]. arX

原创 McGan: Mean and Covariance Feature Matching GAN

文章目錄概主要內容Mean Matching IPMprimedualCovariance Feature Matching IPMprimedual算法代碼 Mroueh Y, Sercu T, Goel V, et al.

原创 Towards Evaluating the Robustness of Neural Networks

文章目錄概主要內容基本的概念目標函數如何選擇c如何應對Box約束L2L_2L2​ attackL0L_0L0​ attackL∞L_{\infty}L∞​ attack Nicholas Carlini, David Wagne

原创 DEEP DOUBLE DESCENT: WHERE BIGGER MODELS AND MORE DATA HURT

文章目錄概主要內容Effective Model Complexity(EMC)label noisedata augmentation下降方式SGD vs AdamAdamSGDSGD + Momentumearly-stopp

原创 Generating Adversarial Examples with Adversarial Networks

文章目錄概主要內容black-box 拓展 Xiao C, Li B, Zhu J, et al. Generating Adversarial Examples with Adversarial Networks[J]. ar

原创 AT-GAN: A Generative Attack Model for Adversarial Transferring on Generative Adversarial Nets

文章目錄概主要內容符號說明Original GeneratorTransfer the Generator Wang X., He K., Guo C., Weinberger K., Hopcroft H., AT-GAN:

原创 ADAM : A METHOD FOR STOCHASTIC OPTIMIZATION

文章目錄概主要內容算法選擇合適的參數一些別的優化算法AdaMax理論代碼 Kingma D P, Ba J. Adam: A Method for Stochastic Optimization[J]. arXiv: Learn

原创 IMPROVING ADVERSARIAL ROBUSTNESS REQUIRES REVISITING MISCLASSIFIED EXAMPLES

文章目錄概主要內容符號MART Wang Y, Zou D, Yi J, et al. Improving Adversarial Robustness Requires Revisiting Misclassified Exa

原创 Universal adversarial perturbations

文章目錄概主要內容算法實驗部分實驗1實驗2實驗3代碼 Moosavidezfooli S, Fawzi A, Fawzi O, et al. Universal Adversarial Perturbations[C]. com