43 citations · 92 across the 13 of their papers we have counts for
6 papers · 1 filter
MOEA/D with Uniformly Randomly Adaptive Weights
Lucas R. C. de Farias, Pedro H. M. Braga, Hansenclever F. Bassani +1
When working with decomposition-based algorithms, an appropriate set of weights might improve quality of the final solution. A set of uniformly distributed weights usually leads to…
Self-Organizing Maps with Variable Input Length for Motif Discovery and Word Segmentation
Raphael C. Brito, Hansenclever F. Bassani
Time Series Motif Discovery (TSMD) is defined as searching for patterns that are previously unknown and appear with a given frequency in time series. Another problem strongly relat…
Incremental Semantic Mapping with Unsupervised On-line Learning
Ygor C. N. Sousa, Hansenclever F. Bassani
This paper introduces an incremental semantic mapping approach, with on-line unsupervised learning, based on Self-Organizing Maps (SOM) for robotic agents. The method includes a ma…
A Semi-Supervised Self-Organizing Map with Adaptive Local Thresholds
Pedro H. M. Braga, Hansenclever F. Bassani
In the recent years, there is a growing interest in semi-supervised learning, since, in many learning tasks, there is a plentiful supply of unlabeled data, but insufficient labeled…
A Semi-Supervised Self-Organizing Map for Clustering and Classification
Pedro H. M. Braga, Hansenclever F. Bassani
There has been an increasing interest in semi-supervised learning in the recent years because of the great number of datasets with a large number of unlabeled data but only a few l…
A Neural Network Architecture for Learning Word-Referent Associations in Multiple Contexts
Hansenclever F. Bassani, Aluizio F. R. Araujo
This article proposes a biologically inspired neurocomputational architecture which learns associations between words and referents in different contexts, considering evidence coll…