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ORCIDSan Gultekin
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Books and Theses
- 2019
[b1]San Gultekin:
Dynamic Machine Learning with Least Square Objectives. Columbia University, USA, 2019
Journal Articles
- 2020
- [j4]San Gultekin
, Avishek Saha, Adwait Ratnaparkhi, John W. Paisley:
MBA: Mini-Batch AUC Optimization. IEEE Trans. Neural Networks Learn. Syst. 31(12): 5561-5574 (2020) - 2019
- [j3]San Gultekin, John W. Paisley:
Online Forecasting Matrix Factorization. IEEE Trans. Signal Process. 67(5): 1223-1236 (2019) - 2017
- [j2]San Gultekin, John W. Paisley:
Nonlinear Kalman Filtering With Divergence Minimization. IEEE Trans. Signal Process. 65(23): 6319-6331 (2017) - 2014
- [j1]Suat Bayram, San Gultekin, Sinan Gezici:
Noise enhanced hypothesis-testing according to restricted Neyman-Pearson criterion. Digit. Signal Process. 25: 17-27 (2014)
Conference and Workshop Papers
- 2021
- [c7]Wei Zhang, Brendan Kitts, Yanjun Han, Zhengyuan Zhou, Tingyu Mao, Hao He, Shengjun Pan, Aaron Flores, San Gultekin, Tsachy Weissman:
MEOW: A Space-Efficient Nonparametric Bid Shading Algorithm. KDD 2021: 3928-3936 - [c6]Tian Zhou, Hao He, Shengjun Pan, Niklas Karlsson, Bharatbhushan Shetty, Brendan Kitts, Djordje Gligorijevic, San Gultekin, Tingyu Mao, Junwei Pan, Jianlong Zhang, Aaron Flores:
An Efficient Deep Distribution Network for Bid Shading in First-Price Auctions. KDD 2021: 3996-4004 - 2020
- [c5]San Gultekin, John W. Paisley:
Risk Bounds for Low Cost Bipartite Ranking. UAI 2020: 959-968 - 2018
- [c4]San Gultekin, Aonan Zhang, John W. Paisley:
Asymptotic Simulated Annealing for Variational Inference. GLOBECOM 2018: 1-7 - 2016
- [c3]Aonan Zhang, San Gultekin, John W. Paisley:
Stochastic Variational Inference for the HDP-HMM. AISTATS 2016: 800-808 - 2014
- [c2]San Gultekin, John W. Paisley:
A Collaborative Kalman Filter for Time-Evolving Dyadic Processes. ICDM 2014: 140-149 - 2012
- [c1]Suat Bayram, San Gultekin, Sinan Gezici:
Noise enhanced detection in restricted Neyman-Pearson framework. SPAWC 2012: 575-579
Informal and Other Publications
- 2023
- [i7]San Gultekin, Brendan Kitts, Aaron Flores, John W. Paisley:
Nonlinear Kalman Filtering with Reparametrization Gradients. CoRR abs/2303.04450 (2023) - 2021
- [i6]Tian Zhou, Hao He, Shengjun Pan, Niklas Karlsson, Bharatbhushan Shetty, Brendan Kitts, Djordje Gligorijevic, San Gultekin, Tingyu Mao, Junwei Pan, Jianlong Zhang, Aaron Flores:
An Efficient Deep Distribution Network for Bid Shading in First-Price Auctions. CoRR abs/2107.06650 (2021) - 2020
- [i5]Shengjun Pan, Brendan Kitts, Tian Zhou, Hao He, Bharatbhushan Shetty, Aaron Flores, Djordje Gligorijevic, Junwei Pan, Tingyu Mao, San Gultekin, Jianlong Zhang:
Bid Shading by Win-Rate Estimation and Surplus Maximization. CoRR abs/2009.09259 (2020) - 2019
- [i4]San Gultekin, John W. Paisley:
Risk Bounds for Low Cost Bipartite Ranking. CoRR abs/1912.00537 (2019) - 2018
- [i3]San Gultekin, Avishek Saha, Adwait Ratnaparkhi, John W. Paisley:
MBA: Mini-Batch AUC Optimization. CoRR abs/1805.11221 (2018) - 2017
- [i2]San Gultekin, John W. Paisley:
Online Forecasting Matrix Factorization. CoRR abs/1712.08734 (2017) - 2015
- [i1]San Gultekin, John W. Paisley:
A Collaborative Kalman Filter for Time-Evolving Dyadic Processes. CoRR abs/1501.05624 (2015)
Coauthor Index
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