منابع مشابه
Semi-Supervised Learning with Competitive Infection Models
The goal in semi-supervised learning is to effectively combine labeled and unlabeled data. One way to do this is by encouraging smoothness across edges in a graph whose nodes correspond to input examples. In many graphbased methods, labels can be thought of as propagating over the graph, where the underlying propagation mechanism is based on random walks or on averaging dynamics. While theoreti...
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In this paper, we propose a new supervised learning method whereby information is controlled by the associated cost in an intermediate layer, and in an output layer, errors between targets and outputs are minimized. In the intermediate layer, competition is realized by maximizing mutual information between input patterns and competitive units with Gaussian functions. The process of information ...
متن کاملSupervised Competitive Learning with Backpropagation Network and Fuzzy Logic
SCL assembles a set of learning modules into a supervised learning system to address the stability-plasticity dilemma. Each learning module acts as a similarity detector for a prototype, and includes prototype resetting (akin to that of ART) to respond to new prototypes. Here (Part I) we report SCL results using backpropagation networks as the learning modules. We used two feature extractors: a...
متن کاملSupervised Competitive Learning for Finding Positions of Radial Basis Functions
This paper introduces the magnetic neural gas (MNG) algorithm, which extends unsupervised competitive learning with class information to improve the positioning of radial basis functions. The basic idea of MNG is to discover heterogeneous clusters (i.e., clusters with data from different classes) and to migrate additional neurons towards them. The discovery is effected by a heterogeneity coeffi...
متن کاملa semi-supervised human action learning
exploiting multimodal information like acceleration and heart rate is a promising method to achieve human action recognition. a semi-supervised action recognition approach aucc (action understanding with combinational classifier) using the diversity of base classifiers to create a high-quality ensemble for multimodal human action recognition is proposed in this paper. furthermore, both labeled ...
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ژورنال
عنوان ژورنال: Journal of Intelligent Material Systems and Structures
سال: 1994
ISSN: 1045-389X,1530-8138
DOI: 10.1177/1045389x9400500209