| A kernel view of the dimensionality reduction of manifolds J Ham, DD Lee, S Mika, B Schölkopf Proceedings of the twenty-first international conference on Machine learning, 47, 2004 | 620 | 2004 |
| Grassmann discriminant analysis: a unifying view on subspace-based learning J Hamm, DD Lee Proceedings of the 25th international conference on Machine learning, 376-383, 2008 | 564 | 2008 |
| Spectral methods for dimensionality reduction LK Saul, KQ Weinberger, J Hamm, F Sha, DD Lee Semisupervised learning, 293-308, 2006 | 319 | 2006 |
| Semisupervised alignment of manifolds. J Hamm, DD Lee, LK Saul AISTATS, 120-127, 2005 | 306 | 2005 |
| Automated facial action coding system for dynamic analysis of facial expressions in neuropsychiatric disorders J Hamm, CG Kohler, RC Gur, R Verma Journal of neuroscience methods 200 (2), 237-256, 2011 | 211 | 2011 |
| GRAM: A framework for geodesic registration on anatomical manifolds J Hamm, DH Ye, R Verma, C Davatzikos Medical image analysis 14 (5), 633-642, 2010 | 127 | 2010 |
| Learning Privately from Multiparty Data J Hamm, P Cao, M Belkin Proceedings of The 33rd International Conference on Machine Learning (ICML …, 2016 | 110 | 2016 |
| Learning high dimensional correspondences from low dimensional manifolds JH Ham, DD Lee, LK Saul ICML workshop, 2003 | 77 | 2003 |
| Crowd-ML: A Privacy-Preserving Learning Framework for a Crowd of Smart Devices J Hamm, A Champion, G Chen, M Belkin, D Xuan IEEE International Conference on Distributed Computing Systems (ICDCS), 11-20, 2015 | 57 | 2015 |
| Extended Grassmann kernels for subspace-based learning J Hamm, D Lee Advances in neural information processing systems 21, 601-608, 2008 | 52 | 2008 |
| Minimax Filter: Learning to Preserve Privacy from Inference Attacks J Hamm Journal of Machine Learning Research 18, 1-31, 2017 | 50 | 2017 |
| Efficient large deformation registration via geodesics on a learned manifold of images J Hamm, C Davatzikos, R Verma International Conference on Medical Image Computing and Computer-Assisted …, 2009 | 48 | 2009 |
| Automatic annotation of daily activity from smartphone-based multisensory streams J Hamm, B Stone, M Belkin, S Dennis International Conference on Mobile Computing, Applications, and Services …, 2012 | 39 | 2012 |
| Subspace-based learning with Grassmann kernels J Hamm University of Pennsylvania, 2008 | 37 | 2008 |
| Personalized video summarization with human in the loop B Han, J Hamm, J Sim 2011 IEEE Workshop on Applications of Computer Vision (WACV), 51-57, 2011 | 33 | 2011 |
| Learning nonlinear appearance manifolds for robot localization J Ham, Y Lin, DD Lee 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2005 | 32 | 2005 |
| Learning a manifold-constrained map between image sets: applications to matching and pose estimation J Ham, I Ahn, D Lee 2006 IEEE Computer Society Conference on Computer Vision and Pattern …, 2006 | 29 | 2006 |
| Regional manifold learning for deformable registration of brain MR images DH Ye, J Hamm, D Kwon, C Davatzikos, KM Pohl International Conference on Medical Image Computing and Computer-Assisted …, 2012 | 24 | 2012 |
| Preserving Privacy of Continuous High-dimensional Data with Minimax Filters J Hamm International Conference on Artificial Intelligence and Statistics (AISTATS …, 2015 | 23 | 2015 |
| Regional manifold learning for disease classification D Ye, B Desjardins, J Hamm, H Litt, K Pohl IEEE Transactions on Medical Imaging, 2014 | 23 | 2014 |
Lawrence K SaulProfessor of Computer Science and Engineering, UC San DiegoVerified email at cs.ucsd.edu
