Li Wang
Title
Cited by
Cited by
Year
Reversed graph embedding resolves complex single-cell trajectories
X Qiu, Q Mao, Y Tang, L Wang, R Chawla, HA Pliner, C Trapnell
Nature methods 14 (10), 979, 2017
11662017
Reversed graph embedding resolves complex single-cell developmental trajectories
X Qiu, Q Mao, Y Tang, L Wang, R Chawla, H Pliner, C Trapnell
bioRxiv, 110668, 2017
1166*2017
Learning sparse svm for feature selection on very high dimensional datasets
M Tan, L Wang, IW Tsang
Proceedings of the 27th International Conference on Machine Learning (ICML …, 2010
2042010
Towards ultrahigh dimensional feature selection for big data
M Tan, IW Tsang, L Wang
The Journal of Machine Learning Research 15 (1), 1371-1429, 2014
1702014
Semidefinite relaxations for best rank-1 tensor approximations
J Nie, L Wang
SIAM Journal on Matrix Analysis and Applications 35 (3), 1155-1179, 2014
1032014
Dimensionality Reduction Via Graph Structure Learning
Q Mao, L Wang, S Goodison, Y Sun
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge …, 2015
622015
Riemannian pursuit for big matrix recovery
M Tan, IW Tsang, L Wang, B Vandereycken, SJ Pan
Proceedings of the 31st International Conference on Machine Learning (ICML …, 2014
602014
Principal Graph and Structure Learning Based on Reversed Graph Embedding
Q Mao, L Wang, I Tsang
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2016
552016
Regularization Methods for SDP Relaxations in Large Scale Polynomial Optimization
J Nie, L Wang
arXiv preprint arXiv:0909.3551, 2009
55*2009
Matching pursuit LASSO Part I: Sparse recovery over big dictionary
M Tan, IW Tsang, L Wang
Signal Processing, IEEE Transactions on 63 (3), 727-741, 2015
392015
Regularization methods for SDP relaxations in large-scale polynomial optimization
J Nie, L Wang
SIAM Journal on Optimization 22 (2), 408-428, 2012
372012
Minimax sparse logistic regression for very high-dimensional feature selection
M Tan, IW Tsang, L Wang
Neural Networks and Learning Systems, IEEE Transactions on 24 (10), 1609-1622, 2013
362013
Inferring Causal Gene Regulatory Networks from Coupled Single-Cell Expression Dynamics Using Scribe
X Qiu, A Rahimzamani, L Wang, B Ren, Q Mao, T Durham, ...
Cell Systems, 2020
262020
Mapping Vector Field of Single Cells
X Qiu, Y Zhang, D Yang, S Hosseinzadeh, L Wang, R Yuan, S Xu, Y Ma, ...
bioRxiv, 696724, 2019
22*2019
Towards inferring causal gene regulatory networks from single cell expression measurements
X Qiu, A Rahimzamani, L Wang, Q Mao, T Durham, JL McFaline-Figueroa, ...
BioRxiv, 426981, 2018
212018
SimplePPT: A Simple Principal Tree Algorithm
Q Mao, L Yang, L Wang, S Goodison, Y Sun
20*
Wind farm layout optimization based on support vector regression guided genetic algorithm with consideration of participation among landowners
X Ju, F Liu, L Wang, WJ Lee
Energy Conversion and Management 196, 1267-1281, 2019
182019
Probabilistic Dimensionality Reduction via Structure Learning
L Wang, Q Mao
IEEE transactions on pattern analysis and machine intelligence 41 (1), 205-219, 2019
182019
Probabilistic Dimensionality Reduction via Structure Learning
L Wang
arXiv preprint arXiv:1610.04929, 2016
182016
Probabilistic Dimensionality Reduction via Structure Learning
L Wang, Q Mao
18*
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