我们用来自真实分析的思想补充这些见解,以进一步激发投影梯度下降(PGD)作为通用的“一阶攻击”,即,利用有关网络的本地一阶信息的最强攻击。 我们探索了网络架构对对抗鲁棒性的影响,并发现模型能力在这里起着重要的作用。为了可靠地抵抗强大的对抗攻击,网络需要的容量要比仅正确分类良性样本的容量更大。这表明,鞍点...
In this work, we analyse the algorithmic method of projected gradient descent (PGD) as applied to quantum tomography, and benchmark it against a number of existing methods. The state-of-the-art with regards to full quantum tomography methods include the diluted iterative algorithm (DIA)6,7 ...
Projected gradient descentIn this paper we study the performance of the Projected Gradient Descent (PGD) algorithm for ℓ p -constrained least squares problems that arise in the framework of compressed sensing. Relying on the restricted isometry property, we provide convergence guarantees for this ...
In this paper we study the performance of the Projected Gradient Descent (PGD) algorithm for _p -constrained least squares problems that arise in the framework of compressed sensing. Relying on the restricted isometry property, we provide convergence guarantees for this algorithm for the entire range...
Repository files navigation README PGD-PyTorch A PyTorch implementation of Projected Gradient Descent (PGD) adversarial attack generationAbout A PyTorch implementation of Projected Gradient Descent (PGD) adversarial attack generation Resources Readme Activity Stars 0 stars Watchers 0 watching Forks 0...
However, as the algorithm must compute the full gradient on the entire dataset at every iteration, the PGD suffers from high computational cost in the large-scale real hyperspectral image. In this paper, we try to alleviate this problem by introducing a mini-batch gradient descent-based ...
puts forward their shortcoming to know the rank of original matrix.The Projected Gradient Descent based on Soft Thresholding(STPGD),proposed in this paper predicts the rank of unknown matrix using soft thresholding,and iteratives based on projected gradient descent,thus it could estimate the rank ...
The objective function is minimized by Projected Gradient Descent (PGD). Results The algorithm achieves accuracy comparable to methods with customized sampling schemes for accelerated T 2 $$ {}_2 $$ mapping. The results are insensitive to the tunable parameters, and the relaxed background p...
In 2D, it was shown that performing a projected gradient descent (PGD) from a gridded over-parametrized initialization was faster than continuous orthogonal matching pursuit. In this paper, we propose an off-the-grid over-parametrized initialization of the PGD based on OMP that permits to fully...
PROJECTED GRADIENT DESCENT BASED ON SOFT THRESHOLDING IN MATRIX COMPLETIONMC,CS,STPGD,电子技术,通信,数字信号处理Zhao,Yujuan,Zheng,Baoyu,Chen,ShouningVIP电子科学学刊:英文版