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Yi Hong
Yi Hong
Sumo Logic, UCLA
Verified email at cs.ucla.edu - Homepage
Title
Cited by
Cited by
Year
Unsupervised feature selection using clustering ensembles and population based incremental learning algorithm
Y Hong, S Kwong, Y Chang, Q Ren
Pattern Recognition 41 (9), 2742-2756, 2008
1782008
Resampling-based selective clustering ensembles
Y Hong, S Kwong, H Wang, Q Ren
Pattern recognition letters 30 (3), 298-305, 2009
722009
Consensus unsupervised feature ranking from multiple views
Y Hong, S Kwong, Y Chang, Q Ren
Pattern Recognition Letters 29 (5), 595-602, 2008
702008
To combine steady-state genetic algorithm and ensemble learning for data clustering
Y Hong, S Kwong
Pattern Recognition Letters 29 (9), 1416-1423, 2008
552008
Learning assignment order of instances for the constrained k-means clustering algorithm
Y Hong, S Kwong
IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 39 …, 2008
532008
Learning a mixture of sparse distance metrics for classification and dimensionality reduction
Y Hong, Q Li, J Jiang, Z Tu
2011 International Conference on Computer Vision, 906-913, 2011
502011
Unsupervised video shot detection using clustering ensemble with a color global scale-invariant feature transform descriptor
Y Chang, DJ Lee, Y Hong, J Archibald
EURASIP Journal on Image and Video Processing 2008, 1-10, 2007
502007
Unsupervised learning of dictionaries of hierarchical compositional models
J Dai, Y Hong, W Hu, SC Zhu, Y Nian Wu
Proceedings of the IEEE conference on computer vision and pattern …, 2014
272014
Unsupervised learning of compositional sparse code for natural image representation
Y Hong, Z Si, W Hu, SC Zhu, YN Wu
Quarterly of Applied Mathematics, 373-406, 2014
252014
Spatial co-training for semi-supervised image classification
Y Hong, W Zhu
Pattern Recognition Letters 63, 59-65, 2015
212015
A Robust Color Image Quantization Algorithm Based on Knowledge Reuse of K-Means Clustering Ensemble.
Y Chang, DJ Lee, Y Hong, J Archibald, D Liang
Journal of Multimedia 3 (2), 2008
162008
Adaptive population size for univariate marginal distribution algorithm
Y Hong, Q Ren, J Zeng
2005 IEEE Congress on Evolutionary Computation 2, 1396-1402, 2005
162005
Genetic-guided semi-supervised clustering algorithm with instance-level constraints
Y Hong, S Kwong, H Xiong, Q Ren
Proceedings of the 10th annual conference on Genetic and evolutionary …, 2008
152008
Over-Selection: An attempt to boost EDA under small population size
Y Hong, S Kwong, Q Ren, X Wang
2007 IEEE Congress on Evolutionary Computation, 1075-1082, 2007
122007
A comprehensive comparison between real population based tournament selection and virtual population based tournament selection
Y Hong, S Kwong, Q Ren, X Wang
2007 IEEE Congress on Evolutionary Computation, 445-452, 2007
122007
Using deep learning to preserve data confidentiality
W Li, P Meng, Y Hong, X Cui
Applied Intelligence 50 (2), 341-353, 2020
102020
Decision-based median filter using k-nearest noise-free pixels
Y Hong, S Kwong, H Wang
2009 IEEE International Conference on Acoustics, Speech and Signal …, 2009
102009
Optimization of noisy fitness functions with univariate marginal distribution algorithm
Y Hong, Q Ren, J Zeng
2005 IEEE congress on evolutionary computation 2, 1410-1417, 2005
102005
Estimation of distribution algorithms making use of both high quality and low quality individuals
Y Hong, G Zhu, S Kwong, Q Ren
2009 IEEE International Conference on Fuzzy Systems, 1806-1813, 2009
92009
The convergence analysis and specification of the population-based incremental learning algorithm
H Li, S Kwong, Y Hong
Neurocomputing 74 (11), 1868-1873, 2011
82011
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Articles 1–20