Search
Now showing items 41-50 of 166
Graph construction for semi-supervised learning
(Association for the Advancement of Artificial Intelligence - AAAIInternational Joint Conferences on Artificial Intelligence - IJCAISociedad Argentina de Informática e Investigación Operativa - SADIOUniversidad de Buenos Aires - UBAUniversidad Nacional del Sur - UNSMinisterio de Ciencia, Tecnología e Innovación ProductivaConsejo Nacional de Investigaciones Científicas y Técnicas – CONICETBuenos Aires, 2015-07)
Semi-Supervised Learning (SSL) techniques have become very relevant since they require a small set of labeled data. In this scenario, graph-based SSL algorithms provide a powerful framework for modeling manifold structures ...
A flocking-like technique to perform semi-supervised learning
(IEEE Computational Intelligence SocietyChinese Academy of SciencesNational Natural Science Foundation of ChinaBeijing, 2014-07)
We present a nature-inspired semi-supervised learning technique based on the flocking formation of certain living species like birds and fishes. Each data item is treated as an individual in the flock. Starting from random ...
Semi-supervised learning with convolutional neural networks for UAV images automatic recognition
(Elsevier B.V., 2019-09-01)
The annotation of large datasets is an issue whose challenge increases as the number of labeled samples available to train the classifier reduces in comparison to the amount of unlabeled data. In this context, semi-supervised ...
Semi-supervised learning with connectivity-driven convolutional neural networks
(2019-12-01)
The annotation of large datasets is an issue whose challenge increases as the number of labeled samples available to train the classifier reduces in comparison to the amount of unlabeled data. In this context, semi-supervised ...
Robust Active Learning For The Diagnosis Of Parasites
(ELSEVIER SCI LTDOXFORD, 2015)
Semi-supervised learning to support the exploration of association rules
(SpringerCham, 2014)
In the last years, many approaches for post-processing association rules have been proposed. The automatics are simple to use, but they don’t consider users’ subjectivity. Unlike, the approaches that consider subjectivity ...
Semi-supervised learning to support the exploration of association rules
(2014-01-01)
In the last years, many approaches for post-processing association rules have been proposed. The automatics are simple to use, but they don't consider users' subjectivity. Unlike, the approaches that consider subjectivity ...
Semi-supervised learning guided by the modularity measure in complex networks
(ELSEVIER SCIENCE BVAMSTERDAM, 2012)
Semi-supervised learning techniques have gained increasing attention in the machine learning community, as a result of two main factors: (1) the available data is exponentially increasing; (2) the task of data labeling is ...
Robust Multi-class Graph Transduction with higher order regularization
(International Neural Network Society - INNSIEEE Computational Intelligence SocietyKillarney, 2015-07)
Graph transduction refers to a family of algorithms that learn from both labeled and unlabeled examples using a weighted graph and scarce label information via regularization or label propagation. A recent empirical study ...
Etiquetagem de micromensagens no Twitter: uma abordagem linguística
(Universidade Federal de Minas GeraisUFMG, 2012-06-01)
Hashtags are labels used by Twitter members in order to classify messages posted in this social network. They are produced by the users themselves without any interference from the platform, which generates interest in ...