The next, I guess, time period of your research that you tend to focus on is uncovering the fundamental difficulty of learning in recurrent nets. And I thought that the "Learning Long-Term Dependencies with Gradient Descent is Difficult" was a really interesting paper. I thought it was kind...
Changbo Zhu and Huan Xu. Online gradient descent in function space, 2015.Zhu, C. and H. Xu (2015). "Online Gradient Descent in Function Space". In: ArXiv e-prints (cited on pages 114, 116, 120, 121, 124).C. Zhu and H. Xu. Online Gradient Descent in Function Space. arXiv.org...
Gradient descent generalises naturally to Riemannian manifolds, and to hyperbolic n n -space, in particular. Namely, having calculated the gradient at the point on the manifold representing the model parameters, the updated point is obtained by travelling along the geodesic passing in the direction ...
Gradient descent is the core component of deep learning methods (see Chapter 4 for additional exploration). Convolutional neural networks (CNNs), based on a mathematical expression named convolution, are commonly applied in computer vision and natural-language-processing tasks (e.g., intent detection...
“true” cost gradient. Due to its stochastic nature, the path towards the global cost minimum is not “direct” as in Gradient Descent, but may go “zig-zag” if we are visuallizing the cost surface in a 2D space. However, it has been shown that Stochastic Gradient Descent almost ...
所以做gradient descent一个很重要的事情是,要把不同的learning rate下,loss随update次数的变化曲线给可视化出来,看前几次update的走法是什么样子,它可以提醒你该如何调整当前的learning rate的大小,直到出现稳定下降的曲线。Adaptive Learning rates显然这样手动地去调整learning rates很麻烦,因此我们需要有一些自动调整...
For the unstable composite system, the self-turning control algorithm based on hybrid trajectory is designed in this paper. The theory of gradient descent is used for parameter adaptive rate design to realize the real time adjustment of the PID control parameters. A supervised controller is ...
using System; namespace LogisticGradient { class LogisticGradientProgram { static void Main(string[] args) { Console.WriteLine("Begin classification demo"); Console.WriteLine("Demonstrating gradient descent"); ... Console.WriteLine("End demo"); Console.ReadLine(); } static double[][] MakeAllData...
An in-depth explanation of Gradient Descent, and how to avoid the problems of local minima and saddle points.
Learn more about the MetalPerformanceShaders.MPSCnnLocalContrastNormalizationGradientNode in the MetalPerformanceShaders namespace.