Gungor Polatkan

20 papers A* 2A 3B 2Journal 11Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	360Brew: A Decoder-only Foundation Model for Personalized Ranking and Recommendation. CoRR Hamed Firooz, Maziar Sanjabi, Adrian Englhardt, Aman Gupta, Ben Levine, Dre Olgiati, Gungor Polatkan, Iuliia Melnychuk, Karthik Ramgopal, Kirill Talanine, Kutta Srinivasan, Luke Simon, Natesh Sivasubramoniapillai, Necip Fazil Ayan, Qingquan Song, Samira Sriram, Souvik Ghosh, Tao Song, Vignesh Kothapalli, Xiaoling Zhai, Ya Xu, Yu Wang, Yun Dai
2021	J	`jnl`	An Attentive Survey of Attention Models. ACM Trans. Intell. Syst. Technol. Sneha Chaudhari, Varun Mithal, Gungor Polatkan, Rohan Ramanath
2021	A*	`conf`	Lambda Learner: Fast Incremental Learning on Data Streams. KDD Rohan Ramanath, Konstantin Salomatin, Jeffrey D. Gee, Kirill Talanine, Onkar Dalal, Gungor Polatkan, Sara Smoot, Deepak Kumar
2020	J	`jnl`	Lambda Learner: Fast Incremental Learning on Data Streams. CoRR Rohan Ramanath, Konstantin Salomatin, Jeffrey D. Gee, Kirill Talanine, Onkar Dalal, Gungor Polatkan, Sara Smoot, Deepak Kumar
2019	J	`jnl`	An Attentive Survey of Attention Models. CoRR Sneha Chaudhari, Gungor Polatkan, Rohan Ramanath, Varun Mithal
2019	A	`conf`	Learning to be Relevant: Evolution of a Course Recommendation System. CIKM Shivani Rao, Konstantin Salomatin, Gungor Polatkan, Mahesh Joshi, Sneha Chaudhari, Vladislav Tcheprasov, Jeffrey D. Gee, Deepak Kumar
2018	J	`jnl`	Deploying Deep Ranking Models for Search Verticals. CoRR Rohan Ramanath, Gungor Polatkan, Liqin Xu, Harold Lee, Bo Hu, Shan Zhou
2018	A	`conf`	Towards Deep and Representation Learning for Talent Search at LinkedIn. CIKM Rohan Ramanath, Hakan Inan, Gungor Polatkan, Bo Hu, Qi Guo, Cagri Ozcaglar, Xianren Wu, Krishnaram Kenthapadi, Sahin Cem Geyik
2018	J	`jnl`	Towards Deep and Representation Learning for Talent Search at LinkedIn. CoRR Rohan Ramanath, Hakan Inan, Gungor Polatkan, Bo Hu, Qi Guo, Cagri Ozcaglar, Xianren Wu, Krishnaram Kenthapadi, Sahin Cem Geyik
2015	J	`jnl`	A Bayesian Nonparametric Approach to Image Super-Resolution. IEEE Trans. Pattern Anal. Mach. Intell. Gungor Polatkan, Mingyuan Zhou, Lawrence Carin, David M. Blei, Ingrid Daubechies
2014	J	`jnl`	Painting Analysis Using Wavelets and Probabilistic Topic Models. CoRR Tong Wu, Gungor Polatkan, David Steel, William P. Brown, Ingrid Daubechies, A. Robert Calderbank
2013	J	`jnl`	Deep Learning with Hierarchical Convolutional Factor Analysis. IEEE Trans. Pattern Anal. Mach. Intell. Bo Chen, Gungor Polatkan, Guillermo Sapiro, David M. Blei, David B. Dunson, Lawrence Carin
2013	B	`conf`	Painting analysis using wavelets and probabilistic topic models. ICIP Tong Wu, Gungor Polatkan, David Steel, William P. Brown, Ingrid Daubechies, A. Robert Calderbank
2012	J	`jnl`	A Bayesian Nonparametric Approach to Image Super-resolution CoRR Gungor Polatkan, Mingyuan Zhou, Lawrence Carin, David M. Blei, Ingrid Daubechies
2012	J	`jnl`	Compressed Inference for Probabilistic Sequential Models CoRR Gungor Polatkan, Oncel Tuzel
2012	—	`—`	Extracting Information from High-Dimensional Data: Probabilistic Modeling, Inference and Evaluation Gungor Polatkan
2011	A	`conf`	Compressed Inference for Probabilistic Sequential Models. UAI Gungor Polatkan, Oncel Tuzel
2011	A*	`conf`	The Hierarchical Beta Process for Convolutional Factor Analysis and Deep Learning. ICML Bo Chen, Gungor Polatkan, Guillermo Sapiro, David B. Dunson, Lawrence Carin
2009	B	`conf`	Detection of forgery in paintings using supervised learning. ICIP Gungor Polatkan, Sina Jafarpour, Andrei Brasoveanu, Shannon M. Hughes, Ingrid Daubechies
2009	—	`conf`	Stylistic analysis of paintings usingwavelets and machine learning. EUSIPCO Sina Jafarpour, Gungor Polatkan, Eugene Brevdo, Shannon M. Hughes, Andrei Brasoveanu, Ingrid Daubechies