منابع مشابه
Convolutional Neural Network Architecture Seach with Q-Learning
We seeks to automate the process of designing the architecture of the convolutional neural network using reinforcemnet learning. The Qlearning agent is trained to sequentially select the CNN layers to achieve maximum accuracy on the validation set. We limited the layers that the agent can select the convolutional layers, the maximum pooling layers, and the softmax layer with pre-defined hyperpa...
متن کاملRobust Neural Network Regression for Offline and Online Learning
We replace the commonly used Gaussian noise model in nonlinear regression by a more flexible noise model based on the Student-tdistribution. The degrees of freedom of the t-distribution can be chosen such that as special cases either the Gaussian distribution or the Cauchy distribution are realized. The latter is commonly used in robust regression. Since the t-distribution can be interpreted as...
متن کاملGlobal Feedforward Neural Network Learning for Classification and Regression
This paper addresses the issues of global optimality and training of a Feedforward Neural Network (FNN) error funtion incorporating the weight decay regularizer. A network with a single hiddenlayer and a single output-unit is considered. Explicit vector and matrix canonical forms for the Jacobian and Hessian of the network are presented. Convexity analysis is then performed utilizing the known ...
متن کاملA general regression neural network
A memory-based network that provides estimates of continuous variables and converges to the underlying (linear or nonlinear) regression surface is described. The general regression neural network (GRNN) is a one-pass learning algorithm with a highly parallel structure. It is shown that, even with sparse data in a multidimensional measurement space, the algorithm provides smooth transitions from...
متن کاملLearning Document Image Features With SqueezeNet Convolutional Neural Network
The classification of various document images is considered an important step towards building a modern digital library or office automation system. Convolutional Neural Network (CNN) classifiers trained with backpropagation are considered to be the current state of the art model for this task. However, there are two major drawbacks for these classifiers: the huge computational power demand for...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Neural Network World
سال: 2018
ISSN: 1210-0552,2336-4335
DOI: 10.14311/nnw.2018.28.023