| Manifold learning: The price of normalization. Y Goldberg, A Zakai, D Kushnir, Y Ritov Journal of Machine Learning Research 9 (8), 2008 | 110 | 2008 |
| Fast multiscale clustering and manifold identification D Kushnir, M Galun, A Brandt Pattern Recognition 39 (10), 1876-1891, 2006 | 110 | 2006 |
| Computation and visualization of cell–cell signaling topologies in single-cell systems data using Connectome MSB Raredon, J Yang, J Garritano, M Wang, D Kushnir, JC Schupp, ... Scientific Reports 12 (1), 4187, 2022 | 107 | 2022 |
| Prediction of subscriber churn using social network analysis C Phadke, H Uzunalioglu, VB Mendiratta, D Kushnir, D Doran Bell Labs Technical Journal 17 (4), 63-76, 2013 | 92 | 2013 |
| Anisotropic diffusion on sub-manifolds with application to earth structure classification D Kushnir, A Haddad, RR Coifman Applied and Computational Harmonic Analysis 32 (2), 280-294, 2012 | 76 | 2012 |
| Root cause analysis for service degradation in computer networks D Kushnir, A Akyamac, V Mendiratta, H Uzunalioglu, D Doran US Patent 9,424,121, 2016 | 59 | 2016 |
| Parametrization of linear systems using diffusion kernels R Talmon, D Kushnir, RR Coifman, I Cohen, S Gannot IEEE Transactions on Signal Processing 60 (3), 1159-1173, 2011 | 58 | 2011 |
| Efficient multilevel eigensolvers with applications to data analysis tasks D Kushnir, M Galun, A Brandt IEEE transactions on pattern analysis and machine intelligence 32 (8), 1377-1391, 2009 | 46 | 2009 |
| A highly accurate solver for stiff ordinary differential equations D Kushnir, V Rokhlin SIAM Journal on Scientific Computing 34 (3), A1296-A1315, 2012 | 34 | 2012 |
| Texture separation via a reference set A Haddad, D Kushnir, RR Coifman Applied and Computational Harmonic Analysis 36 (2), 335-347, 2014 | 29 | 2014 |
| Geometry of intensive scalar dissipation events in turbulence D Kushnir, J Schumacher, A Brandt Physical review letters 97 (12), 124502, 2006 | 29 | 2006 |
| Method and apparatus for determining user satisfaction with services provided in a communication network H Uzunalioglu, JJ Spiess, D Kushnir US Patent App. 13/853,760, 2014 | 20 | 2014 |
| Diffusion-based deep active learning D Kushnir, L Venturi arXiv preprint arXiv:2003.10339, 2020 | 17 | 2020 |
| Detecting and predicting outages in mobile networks with log data VK Gurbani, D Kushnir, V Mendiratta, C Phadke, E Falk, R State 2017 IEEE International Conference on Communications (ICC), 1-7, 2017 | 17 | 2017 |
| System and method for generating subscriber churn predictions CA Phadke, H Uzunalioglu, VB Mendiratta, D Kushnir, D Doran US Patent 8,804,929, 2014 | 17 | 2014 |
| Causality inference for failures in NFV D Kushnir, M Goldstein 2016 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS …, 2016 | 16 | 2016 |
| Alarm causality templates for network function virtualization D Kushnir US Patent 9,836,952, 2017 | 15 | 2017 |
| Classification of device problems of customer premises devices D Kushnir, Y Geng, A Akyamac, C Phadke, H Uzunalioglu US Patent App. 14/242,161, 2015 | 14 | 2015 |
| Active-transductive learning with label-adapted kernels D Kushnir Proceedings of the 20th ACM SIGKDD international conference on Knowledge …, 2014 | 13 | 2014 |
| Method and apparatus for deriving composite tie metric for edge between nodes of a telecommunication call graph VB Mendiratta, D Doran, C Phadke, H Uzunalioglu, D Kushnir US Patent 9,159,077, 2015 | 9 | 2015 |
Huseyin UzunaliogluVerified email at nokia-bell-labs.com
