Name
Affiliation
Papers
YONG LIU
Univ Univ Aizu, Fukushima 9658580, Japan
84
Collaborators
Citations 
PageRank 
59
2526
265.08
Referers 
Referees 
References 
4105
483
523
Search Limit
1001000
Title
Citations
PageRank
Year
Self-admitted technical debt detection by learning its comprehensive semantics via graph neural networks00.342022
Awareness and Cooperation in Neural Network Ensemble Learning00.342019
Combining Two Negatively Correlated Learning Signals in a Committee Machine00.342018
Negative Correlation Learning with Multiple Target Values00.342018
Learning Targets for Building Cooperation Awareness in Ensemble Learning00.342018
Build Correlation Awareness In Negative Correlation Learning00.342017
Random Separation Learning For Neural Network Ensembles00.342017
Computational awareness for learning neural network ensembles10.412017
Hybrid Negative Correlation Learning With Randomly Splitting Data00.342017
Low-Cost and Steady On-Line Retraining of MLP with Guide Data.00.342017
Dbm Vs Elm: A Study On Effective Training Of Compact Mlp00.342016
Guide Data Generation For On-Line Learning Of Dbm-Initialized Mlp00.342016
Learning self-awareness in committee machines00.342016
Enforcing Negativity In Negative Correlation Learning00.342016
Bounded Learning For Neural Network Ensembles10.412015
Improving the Performance of the Decision Boundary Making Algorithm via Outlier Detection.40.632015
Strategies for determining effective step size of the backpropagation algorithm for on-line learning00.342015
A modified cuckoo search algorithm for flow shop scheduling problem with blocking00.342015
Negative Correlation Learning with Difference Learning.00.342015
Error awareness by lower and upper bounds in ensemble learning20.462015
Ensemble Learning with Correlation-Based Penalty00.342014
From low negative correlation learning to high negative correlation learning10.412014
Improving performance of decision boundary making with support vector machine based outlier detection00.342014
A comprehensive analysis on optimization performance of chaotic evolution and its parameter distribution00.342014
Study on the effect of learning parameters on decision boundary making algorithm10.392014
Control of correlation in negative correlation learning00.342014
New discoveries in balanced ensemble learning00.342012
Balancing Ensemble Learning between Known and Unknown Data00.342012
Enhancing particle swarm optimization using generalized opposition-based learning1092.652011
Measurements In Fast Evolutionary Programming00.342010
Are Long Jumps Of Cauchy Mutations Effective In Fast Evolutionary Programming?00.342010
A Particle Swarm Optimization Algorithm Based on Genetic Selection Strategy00.342009
Balanced Learning for Ensembles with Small Neural Networks50.672009
Space transformation search: a new evolutionary technique351.432009
A Balanced Ensemble Learning with Adaptive Error Functions80.992008
Particle Swarm Optimization with a Novel Multi-Parent Crossover Operator70.482008
An improved Particle Swarm Optimization with adaptive jumps70.552008
Correlation between Mutations and Self-adaptation in Evolutionary Programming10.362008
Reduction Of Difference Among Trained Neural Networks By Re-Learning00.342008
Fast multi-swarm optimization with cauchy mutation and crossover operation60.522007
Evolvable Systems: From Biology to Hardware, 7th International Conference, ICES 2007, Wuhan, China, September 21-23, 2007, Proceedings412.992007
A Hybrid Particle Swarm Algorithm with Cauchy Mutation412.162007
A fast particle swarm optimization algorithm with cauchy mutation and natural selection strategy221.182007
Advances in Computation and Intelligence, Second International Symposium, ISICA 2007, Wuhan, China, September 21-23, 2007, Proceedings686.632007
Operator adaptation in evolutionary programming30.452007
Evolving Neural Network Ensembles by Fitness Sharing20.382006
Create Stable Neural Networks By Cross-Validation80.712006
How to stop the evolutionary process in evolving neural network ensembles20.382006
Make fast evolutionary programming robust by search step control00.342006
Current developments and future directions of bio-inspired computation and implications for ecoinformatics50.462006
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