Despite considerable achievements of deep learning-based side-channel analysis, overfitting represents a significant obstacle in finding optimized neural network models. This issue is not unique to the side-cha
Mathematical consequences of orthogonal weights initialization and regularization in deep learning. Experiments with gain-adjusted orthogonal regularizer on RNNs with SeqMNIST dataset. - GitHub - EsterHlav/Dynamical-Isometry-from-Orthogonality-Neural-Ne
: return l1_regularizer(scale_l1, scope) return sum_regularizer([l1_regularizer(scale_l1), l2_regularizer(scale_l2)], scope=scope) # 将多个 reg 函数求和 # 输入一系列 reg 函数,返回一个 reg 函数 def sum_regularizer(regularizer_list, scope=None): regularizer_list = [reg for reg in ...
In conservative Q-learning the regularizer that is added to the critic loss relies on the difference between the expected Q-values of the actions from the current policy and the Q-values of the actions from the data set. References [1] Kumar, Aviral, Aurick Zhou, George Tucker, and Sergey...
perspective of generic DNNs. Such a perspective enables us to study deep multi-view learning in the context of regularized network training, for which we present control experiments of benchmark image classification to show the efficacy of our proposed CorrReg. To investigate how CorrReg is useful...
b) ConR adds additional loss weight for minority, and mis-labelled examples, resulting in better feature representations and c) better prediction error. Quick Preview ConR is complementary to conventional imbalanced learning techniques. The following code snippent shows the implementation of ConR ...
Benefiting from the deep convolutional neural network that can discover the true representations hidden in massive natural images, deep learning based methods [21], [22], [23], [32], [33], [34], [35] have been proposed and successfully applied to handle the image super resolution inverse ...
Deep CNN and Deep GAN in Computational Visual Perception-Driven Image Analysis 2021, Complexity Classification of arrhythmia by using deep learning with 2-D ECG spectral image representation 2020, Remote Sensing Spatial prior fuzziness pool-based interactive classification of hyperspectral images 2019, Remo...
DNN(Deep-Learning Neural Network) 欲上青天揽明月 实战MNN之量化部署 糖心他爸 MNN代码走读 MNN是开源边缘AI计算框架的一种,内部有很多值得学习的设计理念和代码实现。这个章节是我从工程实现角度走读源码的笔记。 文章部分内容利用GPT做过整理润色能力架构图模块解释 Pre-Inferenc… Justi...发表于高性能工作打开...
Transferring a low-dynamic-range (LDR) image to a high-dynamic-range (HDR) image, which is the so-called inverse tone mapping (iTM), is an important imaging technique to improve visual effects of imaging devices. In this paper, we propose a novel deep learning-based iTM method, which lea...