风格化ImageNet训练 (Stylized ImageNet Training):在风格化ImageNet (SIN) 上进行预训练,这可以看作是一种极端形式的增强,它破坏了纹理和类别标签之间的相关性(SHAPENET)[18]。 对抗性训练 (Adversarial Training):针对PGD(Projected Gradient Descent)对手进行对抗性训练的模型,这种训练通过逐渐增加攻击预算ϵ来提高...
heart, and remaining eye artifacts were automatically organized and removed by using an Independent component analysis (ICA) based Multiple Artifact Rejection Algorithm (MARA82,83). To interpolate the absent and removed channels, a spherical method was used. The neurophysiological...
When weights in each layer are initialized from a Gaussian distribution \({\mathcal{N}}(0,{\sigma }_{W}^{2})\) and the size of hidden layers tend to infinity, the function f(x, θ) learned by training the network parameters θ with gradient descent on a squared loss to zero ...
neural net- works, many theoretical breakthroughs have been made progressively, including studying the properties of stochas- tic gradient descent [31], different complexity measures [46], generalization gaps [50], and many more from differ- ent mod...
This called for a “rethinking” ofconventional, algorithm-independent techniques to explain generalization. Specif ically, it was arguedthat learning-theoretic approaches must be reformed by identifying and incorporating the implicitbias/regularization of stochastic gradient descent (SGD) [ 6 , 35 , ...
For each empirical spectral tuning curve, the best fit parameters of the model are iteratively estimated using a standard gradient descent algorithm under the least squares estimation method. We consider a set ofNobservations of the activities of third order cellsY = (y1,y2, …yN) that wer...
In this section, we present a novel algorithm for computing the Trajectory Shapley value. We name the proposed framework Trajectory Shapley, as it combines trajectory flow tensors and Shapley values. 4.1. Trajectory Shapley While we extract the trajectory flow tensor and reduce the computational comp...