Feng Liang
Feng Liang
Department of Statistics
Bestätigte E-Mail-Adresse bei
Zitiert von
Zitiert von
Mixtures of g Priors for Bayesian Variable Selection
F Liang, R Paulo, G Molina, MA Clyde, JO Berger
Journal of the American Statistical Association 103 (481), 410-423, 2008
Accelerating magnetic resonance imaging via deep learning
S Wang, Z Su, L Ying, X Peng, S Zhu, F Liang, D Feng, D Liang
2016 IEEE 13th international symposium on biomedical imaging (ISBI), 514-517, 2016
Learning locally-adaptive decision functions for person verification
Z Li, S Chang, F Liang, TS Huang, L Cao, JR Smith
Proceedings of the IEEE conference on computer vision and pattern …, 2013
On community outliers and their efficient detection in information networks
J Gao, F Liang, W Fan, C Wang, Y Sun, J Han
Proceedings of the 16th ACM SIGKDD international conference on Knowledge …, 2010
Hierarchical gaussianization for image classification
X Zhou, N Cui, Z Li, F Liang, TS Huang
2009 IEEE 12th International Conference on Computer Vision, 1971-1977, 2009
Permutation tests for classification
P Golland, F Liang, S Mukherjee, D Panchenko
International conference on computational learning theory, 501-515, 2005
Graph-based consensus maximization among multiple supervised and unsupervised models
J Gao, F Liang, W Fan, Y Sun, J Han
Advances in Neural Information Processing Systems 22, 2009
Heterogeneous feature machines for visual recognition
L Cao, J Luo, F Liang, TS Huang
2009 IEEE 12th International Conference on Computer Vision, 1095-1102, 2009
Improved minimax predictive densities under Kullback-Leibler loss
EI George, F Liang, X Xu
The Annals of Statistics, 78-91, 2006
An integrated framework on mining logs files for computing system management
T Li, F Liang, S Ma, W Peng
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge …, 2005
Characterizing the Function Space for Bayesian Kernel Models.
NS Pillai, Q Wu, F Liang, S Mukherjee, RL Wolpert
Journal of Machine Learning Research 8 (8), 2007
Exact minimax strategies for predictive density estimation, data compression and model selection
F Liang, A Barron
The 2002 IEEE International Symposium on Information Theory (ISIT), 2002
A graph-based consensus maximization approach for combining multiple supervised and unsupervised models
J Gao, F Liang, W Fan, Y Sun, J Han
IEEE Transactions on Knowledge and Data Engineering 25 (1), 15-28, 2011
The use of unlabeled data in predictive modeling
F Liang, S Mukherjee, M West
Statistical Science 22 (2), 189-205, 2007
Quantifying model structural error: Efficient B ayesian calibration of a regional groundwater flow model using surrogates and a data‐driven error model
T Xu, AJ Valocchi, M Ye, F Liang
Water Resources Research 53 (5), 4084-4105, 2017
Localized sliced inverse regression
Q Wu, F Liang, S Mukherjee
Journal of Computational and Graphical Statistics 19 (4), 843-860, 2010
Bayesian Regularization for Graphical Models With Unequal Shrinkage
L Gan, N Narisetty, F Liang
Journal of the American Statistical Association, …, 2018
Nonparametric Bayesian kernel models
F Liang, K Mao, M Liao, S Mukherjee, M West
Department of Statistical Science, Duke University, Discussion Paper, 07-10, 2007
Systems and methods for discovering fully dependent patterns
S Ma, JL Hellerstein, F Liang
US Patent 6,990,486, 2006
Impact of building design parameters on daylighting metrics using an analysis, prediction, and optimization approach based on statistical learning technique
J Lee, M Boubekri, F Liang
Sustainability 11 (5), 1474, 2019
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