Backpropagation with Vector Chaotic Learning Rate
نویسندگان
چکیده
منابع مشابه
Good Learning Performance of Backpropagation Algorithm with Chaotic Noise Features
Over the years, many improvements and modifications of the backpropagation learning algorithm have been reported. In this study, we propose a new modified backpropagation learning algorithm by adding the chaotic noise into weight update process. By computer simulations, we confirm that the proposed algorithm can gives a better convergence rate and can find a good solution in early time compared...
متن کاملAn Improved Backpropagation Method with Adaptive Learning Rate
A method improving the convergence rate of the backpropagation algorithm is proposed. This method adapts the learning rate using the Barzilai and Borwein [IMA J.Numer. Anal., 8, 141–148, 1988] steplength update for gradient descent methods. The determined learning rate is different for each epoch and depends on the weights and gradient values of the previous one. Experimental results show that ...
متن کاملNonmonotone methods for backpropagation training with adaptive learning rate
In this paper, we present nonmonotone methods for feedforward neural network training, i.e. training methods in which error function values are allowed to increase at some iterations. More specifically, at each epoch we impose that the current error function value must satisfy an Armijo-type criterion, with respect to the maximum error function value of M previous epochs. A strategy to dynamica...
متن کاملMeta-Learning with Backpropagation
This paper introduces gradient descent methods applied to meta-leaming (leaming how to leam) in Neural Networks. Meta-leaning has been of interest in the machine leaming field for decades because of its appealing applications to intelligent agents, non-stationary time series, autonomous robots, and improved leaming algorithms. Many previous neural network-based approaches toward meta-leaming ha...
متن کاملLearning Multiagent Communication with Backpropagation
Many tasks in AI require the collaboration of multiple agents. Typically, the communication protocol between agents is manually specified and not altered during training. In this paper we explore a simple neural model, called CommNN, that uses continuous communication for fully cooperative tasks. The model consists of multiple agents and the communication between them is learned alongside their...
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: International Journal of Advanced Computer Science and Applications
سال: 2011
ISSN: 2158-107X,2156-5570
DOI: 10.14569/ijacsa.2011.020414