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Gungor Polatkan
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Cited by
Year
An attentive survey of attention models
S Chaudhari, V Mithal, G Polatkan, R Ramanath
ACM Transactions on Intelligent Systems and Technology (TIST) 12 (5), 1-32, 2021
7182021
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
1402013
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
1002014
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
992009
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
592018
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
592009
The Hierarchical Beta Process for Convolutional Factor Analysis and Deep Learning.
B Chen, G Polatkan, G Sapiro, DB Dunson, L Carin
ICML, 361-368, 2011
522011
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
262007
An attentive survey of attention models. arXiv 2019
S Chaudhari, G Polatkan, R Ramanath, V Mithal
arXiv preprint arXiv:1904.02874, 0
22
Social media data mining and analytics
G Szabo, G Polatkan, PO Boykin, A Chalkiopoulos
John Wiley & Sons, 2018
212018
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
112019
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
112013
Recommendations using session relevance and incremental learning
R Ramanath, K Salomatin, JD Gee, OA Dalal, G Polatkan, SS Gerrard, ...
US Patent App. 16/912,245, 2021
92021
Lambda learner: Fast incremental learning on data streams
R Ramanath, K Salomatin, JD Gee, K Talanine, O Dalal, G Polatkan, ...
Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021
92021
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
92020
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
92019
Feature generation pipeline for machine learning
IICW Lloyd, K Salomatin, JD Gee, MS Joshi, S Rao, V Tcheprasov, ...
US Patent 11,195,023, 2021
82021
Unsupervised learning of entity representations using graphs
R Ramanath, G Polatkan, Q Guo, C Ozcaglar, K Kenthapadi, SC Geyik
US Patent 11,106,979, 2021
82021
Cluster-based collaborative filtering
K Salomatin, F Hedayati, JD Gee, MS Joshi, S Rao, G Polatkan, D Kumar
US Patent 10,887,655, 2021
82021
Generating supervised embedding representations for search
R Ramanath, G Polatkan, Q Guo, C Ozcaglar, K Kenthapadi, SC Geyik
US Patent App. 16/021,639, 2020
72020
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