Results 261 to 270 of about 285,439 (304)

Class imbalance learning via a fuzzy total margin based support vector machine

Applied Soft Computing Journal, 2015
A fuzzy total margin based support vector machine (FTM-SVM) method to handle the class imbalance learning (CIL) problem in the presence of outliers and noise was presented.The proposed method incorporates total margin algorithm, different cost functions and the proper approach of fuzzification of the penalty into FTM-SVM and formulates them in ...
exaly   +2 more sources

Machine Learning Based Approach to Assess Territorial Marginality

2022
The territorial cohesion is one of the primary objectives for the European Union and it affects economic recovery pushing the role of Public Administration in promoting territorial development actions. The National Strategy for Inner Areas (SNAI) is a public policy promoting endogenous development processes in marginal territories with low settlement ...
Simone Corrado, Francesco Scorza
openaire   +2 more sources

Dual Transfer Learning for Neural Machine Translation with Marginal Distribution Regularization

Proceedings of the AAAI Conference on Artificial Intelligence, 2018
Neural machine translation (NMT) heavily relies on parallel bilingual data for training. Since large-scale, high-quality parallel corpora are usually costly to collect, it is appealing to exploit monolingual corpora to improve NMT.
Yijun Wang 0002, Yingce Xia, Li Zhao 0007, Jiang Bian 0002, Tao Qin 0001, Guiquan Liu, Tie-Yan Liu   +6 more
openaire   +1 more source

Large margin strategies in machine learning

2000 IEEE International Symposium on Circuits and Systems. Emerging Technologies for the 21st Century. Proceedings (IEEE Cat No.00CH36353), 2002
Controlling the capacity of a learning system in a way that does not depend on the dimensionality of the hypothesis space provides the key for effectively using large neural networks and decision trees, ensemble methods and kernel-induced feature spaces.
openaire   +1 more source

Fast large-margin learning for statistical machine translation [PDF]

Int. J. Comput. Linguistics Appl., 2013
Statistical Machine Translation (SMT) can be viewed as a generate-and-select process, where the selection of the best translation is based on multiple numerical features assessing the quality of a translation hypothesis. Training a SMT system consists in finding the right balance between these features, so as to produce the best possible output, and is
Wisniewski, Guillaume, Yvon, François
openaire   +1 more source