Yan-Xing Hu

According to our database1, Yan-Xing Hu authored at least 15 papers between 2011 and 2018.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.



In proceedings 
PhD thesis 


On csauthors.net:


An eigenvector based center selection for fast training scheme of RBFNN.
Inf. Sci., 2018

OWA operator based link prediction ensemble for social network.
Expert Syst. Appl., 2015

A set covering based approach to find the reduct of variable precision rough set.
Inf. Sci., 2014

A hybrid algorithm for recommendation twitter peers.
Proceedings of the Symposium on Applied Computing, 2014

Integrating Local Information-based Link Prediction Algorithms with OWA Operator.
Proceedings of the ICPRAM 2014, 2014

A Further Investigation on the Reliability of Extreme Learning Machines.
Proceedings of the 2014 IEEE International Conference on Data Mining Workshops, 2014

An advancing investigation on reduct and consistency for decision tables in Variable Precision Rough Set models.
Proceedings of the IEEE International Conference on Fuzzy Systems, 2014

Regression ensemble with PSO algorithms based fuzzy integral.
Proceedings of the IEEE Congress on Evolutionary Computation, 2014

Support Vector Regression with Kernel Mahalanobis Measure for Financial Forecast.
Proceedings of the Time Series Analysis, Modeling and Applications, 2013

Application of feature-weighted Support Vector regression using grey correlation degree to stock price forecasting.
Neural Computing and Applications, 2013

An improved model of virtual-currency in social networking sites.
EAI Endorsed Trans. e-Business, 2012

Optimal bandwidth selection for re-substitution entropy estimation.
Applied Mathematics and Computation, 2012

Naive Bayesian Classifier Based on Neighborhood Probability.
Proceedings of the Advances in Computational Intelligence, 2012

A Weighted Support Vector Data Description Based on Rough Neighborhood Approximation.
Proceedings of the 12th IEEE International Conference on Data Mining Workshops, 2012

A comparative study among different kernel functions in flexible naïve Bayesian classification.
Proceedings of the International Conference on Machine Learning and Cybernetics, 2011