Deep learning with hierarchical convolutional factor analysis B Chen, G Polatkan, G Sapiro, D Blei, D Dunson, L Carin IEEE transactions on pattern analysis and machine intelligence 35 (8), 1887-1901, 2013 | 114 | 2013 |
An attentive survey of attention models S Chaudhari, G Polatkan, R Ramanath, V Mithal arXiv preprint arXiv:1904.02874, 2019 | 78 | 2019 |
A Bayesian nonparametric approach to image super-resolution G Polatkan, M Zhou, L Carin, D Blei, I Daubechies IEEE transactions on pattern analysis and machine intelligence 37 (2), 346-358, 2014 | 77 | 2014 |
Detection of forgery in paintings using supervised learning G Polatkan, S Jafarpour, A Brasoveanu, S Hughes, I Daubechies 2009 16th IEEE International Conference on Image Processing (ICIP), 2921-2924, 2009 | 65 | 2009 |
The hierarchical beta process for convolutional factor analysis and deep learning B Chen, G Polatkan, G Sapiro, L Carin, DB Dunson Proceedings of the 28th International Conference on Machine Learning (ICML …, 2011 | 46 | 2011 |
Stylistic analysis of paintings usingwavelets and machine learning S Jafarpour, G Polatkan, E Brevdo, S Hughes, A Brasoveanu, ... 2009 17th European Signal Processing Conference, 1220-1224, 2009 | 42 | 2009 |
Dependence of cooperative vehicle system performance on market penetration SE Shladover, G Polatkan, R Sengupta, J VanderWerf, M Ergen, ... Transportation research record 2000 (1), 121-127, 2007 | 21 | 2007 |
Towards deep and representation learning for talent search at LinkedIn R Ramanath, H Inan, G Polatkan, B Hu, Q Guo, C Ozcaglar, X Wu, ... Proceedings of the 27th ACM International Conference on Information and …, 2018 | 20 | 2018 |
Painting analysis using wavelets and probabilistic topic models T Wu, G Polatkan, D Steel, W Brown, I Daubechies, R Calderbank 2013 IEEE International Conference on Image Processing, 3264-3268, 2013 | 9 | 2013 |
Social media data mining and analytics G Szabo, G Polatkan, PO Boykin, A Chalkiopoulos John Wiley & Sons, 2018 | 7 | 2018 |
Compressed inference for probabilistic sequential models G Polatkan, O Tuzel Uncertainty in Artificial Intelligence (UAI), 2011 Twenty-Seventh Annual …, 2011 | 5 | 2011 |
An attentive survey of attention models. arXiv 2019 S Chaudhari, G Polatkan, R Ramanath, V Mithal arXiv preprint arXiv:1904.02874, 0 | 5 | |
Learning to be Relevant: Evolution of a Course Recommendation System S Rao, K Salomatin, G Polatkan, M Joshi, S Chaudhari, V Tcheprasov, ... Proceedings of the 28th ACM International Conference on Information and …, 2019 | 2 | 2019 |
Deep neural network architecture for search R Ramanath, G Polatkan, L Xu, B Hu, S Zhou, HH Lee US Patent App. 15/941,314, 2019 | 2 | 2019 |
Method for determining compressed state sequences CO Tuzel, G Polatkan US Patent 8,405,531, 2013 | 2 | 2013 |
Generalized linear mixed models for generating recommendations K Salomatin, G Polatkan US Patent App. 16/020,384, 2020 | 1 | 2020 |
Deploying deep ranking models for search verticals R Ramanath, G Polatkan, L Xu, H Lee, B Hu, S Zhou SysML Conference, 2018 | 1 | 2018 |
Lambda Learner: Fast Incremental Learning on Data Streams R Ramanath, K Salomatin, JD Gee, K Talanine, O Dalal, G Polatkan, ... arXiv preprint arXiv:2010.05154, 2020 | | 2020 |
Techniques for querying user profiles using neural networks R Ramanath, G Polatkan, Q Guo, C Ozcaglar, K Kenthapadi, SC Geyik US Patent 10,795,897, 2020 | | 2020 |
Standalone video classification G Polatkan, MS Joshi, F Hedayati, B Bills US Patent 10,740,621, 2020 | | 2020 |