AIMC Topic: Learning

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Consensus-based distributed cooperative learning from closed-loop neural control systems.

IEEE transactions on neural networks and learning systems
In this paper, the neural tracking problem is addressed for a group of uncertain nonlinear systems where the system structures are identical but the reference signals are different. This paper focuses on studying the learning capability of neural net...

Learning feature representations with a cost-relevant sparse autoencoder.

International journal of neural systems
There is an increasing interest in the machine learning community to automatically learn feature representations directly from the (unlabeled) data instead of using hand-designed features. The autoencoder is one method that can be used for this purpo...

The effect of behavioral preferences on skill acquisition in determining unspecified, suitable action patterns to control humanoid robots.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
This research investigated the effect of behavioral preferences on learning efficiency when attempting to determine unspecified, but suitable action sequences for unfamiliar tasks. The goal of this research was to develop a skill acquisition support ...

Feature selection using a neural framework with controlled redundancy.

IEEE transactions on neural networks and learning systems
We first present a feature selection method based on a multilayer perceptron (MLP) neural network, called feature selection MLP (FSMLP). We explain how FSMLP can select essential features and discard derogatory and indifferent features. Such a method...

Efficient training of convolutional deep belief networks in the frequency domain for application to high-resolution 2D and 3D images.

Neural computation
Deep learning has traditionally been computationally expensive, and advances in training methods have been the prerequisite for improving its efficiency in order to expand its application to a variety of image classification problems. In this letter,...