Understanding Convolution in Deep Learning Convolution is probably the most important concept in deep learning right now. It was convolution and convolutional nets that catapulted deep learning to the forefront of almost any machine learning task the…
zh.wikipedia.org/wiki/凸優化 以下问题都是凸优化问题,或可以通过改变变量而转化为凸优化问题:[5] 最小二乘 线性规划 线性约束的二次规划 半正定规划 Convex function Convex minimization is a subfield of optimization that studies the problem of minimizing convex functions over convex sets. The convexity makes opt…
Chapter 1.6 : Information Theory Chapter 1.6 : Information Theory Christopher M. Bishop, PRML, Chapter 1 Introdcution 1. Information h(x) Given a random variable and we ask how much information is received when we observe a specific value for thi…
<Deep Learning> Ian Goodfellow Yoshua Bengio Aaron Courvill 关于此书Part One重难点的个人阅读笔记. 2.7 Eigendecomposition we decompose a matrix into a set of eigenvectors and eigenvalues. 特征值与特征向量: 应用非常广泛: 图像处理中的PCA方法,选取特征值最高的k个特征向量来表示一个矩阵,从而达到降维分析+特征显示的方法, 还有图像压缩…
When training deep neural networks, it is often useful to reduce learning rate as the training progresses. This can be done by using pre-defined learning rate schedules or adaptive learning rate methods. In this article, I train a convolutional neura…
