Heng Huang
Heng Huang
John A. Jurenko Endowed Professor, Electrical and Computer Engineering, University of Pittsburgh
Verified email at pitt.edu
Cited by
Cited by
Efficient and robust feature selection via joint l2, 1-norms minimization
F Nie, H Huang, X Cai, C Ding
Advances in Neural Information Processing Systems 23, 1813-1821, 2010
Multi-view k-means clustering on big data
X Cai, F Nie, H Huang
Twenty-Third International Joint conference on artificial intelligence, 2013
Clustering and projected clustering with adaptive neighbors
F Nie, X Wang, H Huang
Proceedings of the 20th ACM SIGKDD international conference on Knowledge …, 2014
Using smart meter data to improve the accuracy of intraday load forecasting considering customer behavior similarities
FL Quilumba, WJ Lee, H Huang, DY Wang, RL Szabados
IEEE Transactions on Smart Grid 6 (2), 911-918, 2014
The constrained laplacian rank algorithm for graph-based clustering.
F Nie, X Wang, MI Jordan, H Huang
AAAI, 1969-1976, 2016
Robust nonnegative matrix factorization using l21-norm
D Kong, C Ding, H Huang
Proceedings of the 20th ACM international conference on Information and …, 2011
Multi-view clustering and feature learning via structured sparsity
H Wang, F Nie, H Huang
International conference on machine learning, 352-360, 2013
Deep clustering via joint convolutional autoencoder embedding and relative entropy minimization
K Ghasedi Dizaji, A Herandi, C Deng, W Cai, H Huang
Proceedings of the IEEE international conference on computer vision, 5736-5745, 2017
Low-rank matrix recovery via efficient schatten p-norm minimization
F Nie, H Huang, C Ding
Twenty-sixth AAAI conference on artificial intelligence, 2012
Large-scale multi-view spectral clustering via bipartite graph
Y Li, F Nie, H Huang, J Huang
Proceedings of the twenty-ninth AAAI conference on artificial intelligence …, 2015
Robust principal component analysis with non-greedy l1-norm maximization
F Nie, H Huang, C Ding, D Luo, H Wang
IJCAI proceedings-international joint conference on artificial intelligence …, 2011
A convex formulation for semi-supervised multi-label feature selection
X Chang, F Nie, Y Yang, H Huang
Proceedings of the National Conference on Artificial Intelligence, 2014
Heterogeneous image feature integration via multi-modal spectral clustering
X Cai, F Nie, H Huang, F Kamangar
CVPR 2011, 1977-1984, 2011
Optimal mean robust principal component analysis
F Nie, J Yuan, H Huang
International conference on machine learning, 1062-1070, 2014
Multi-view subspace clustering
H Gao, F Nie, X Li, H Huang
Proceedings of the IEEE international conference on computer vision, 4238-4246, 2015
Robust manifold nonnegative matrix factorization
J Huang, F Nie, H Huang, C Ding
ACM Transactions on Knowledge Discovery from Data (TKDD) 8 (3), 1-21, 2014
Multi-label linear discriminant analysis
H Wang, C Ding, H Huang
Computer Vision–ECCV 2010, 126-139, 2010
Identifying quantitative trait loci via group-sparse multitask regression and feature selection: an imaging genetics study of the ADNI cohort
H Wang, F Nie, H Huang, S Kim, K Nho, SL Risacher, AJ Saykin, L Shen, ...
Bioinformatics 28 (2), 229-237, 2012
Sparse representation of whole-brain fMRI signals for identification of functional networks
J Lv, X Jiang, X Li, D Zhu, H Chen, T Zhang, S Zhang, X Hu, J Han, ...
Medical image analysis 20 (1), 112-134, 2015
Sparse multi-task regression and feature selection to identify brain imaging predictors for memory performance
H Wang, F Nie, H Huang, S Risacher, C Ding, AJ Saykin, L Shen
2011 International Conference on Computer Vision, 557-562, 2011
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