| 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 | 1068 | 2008 |
| 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 | 557 | 2013 |
| 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 | 384 | 2016 |
| 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 | 267 | 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 | 184 | 2009 |
| Permutation tests for classification P Golland, F Liang, S Mukherjee, D Panchenko International conference on computational learning theory, 501-515, 2005 | 111 | 2005 |
| 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 | 106 | 2009 |
| Improved minimax predictive densities under Kullback–Leibler loss EI George, F Liang, X Xu The Annals of Statistics 34 (1), 78-91, 2006 | 100 | 2006 |
| 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, 585-593, 2009 | 96 | 2009 |
| 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 | 87 | 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 | 79 | 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 | 73 | 2002 |
| The use of unlabeled data in predictive modeling F Liang, S Mukherjee, M West Statistical Science, 189-205, 2007 | 59 | 2007 |
| 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 | 58 | 2011 |
| Localized sliced inverse regression Q Wu, F Liang, S Mukherjee Journal of Computational and Graphical Statistics 19 (4), 843-860, 2010 | 55 | 2010 |
| 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 | 42 | 2007 |
| Quantifying model structural error: Efficient Bayesian 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 | 35 | 2017 |
| Systems and methods for discovering fully dependent patterns S Ma, JL Hellerstein, F Liang US Patent 6,990,486, 2006 | 35 | 2006 |
| Bayesian Regularization for Graphical Models With Unequal Shrinkage L Gan, N Narisetty, F Liang Journal of the American Statistical Association, https://doi.org/10.1080 …, 2018 | 25 | 2018 |
| Quality of information based data selection and transmission in wireless sensor networks L Su, S Hu, S Li, F Liang, J Gao, TF Abdelzaher, J Han 2012 IEEE 33rd Real-Time Systems Symposium, 327-338, 2012 | 24 | 2012 |
Sayan MukherjeeDuke University, MITVerified email at stat.duke.edu
