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2020 – today
- 2024
[c13]Haleh Akrami, Omar Zamzam, Anand A. Joshi, Sergül Aydöre, Richard M. Leahy:
Beta Quantile Regression for Robust Estimation of Uncertainty in the Presence of Outliers. ICASSP 2024: 7480-7484- [c12]Shuai Tang, Steven Wu, Sergül Aydöre, Michael Kearns, Aaron Roth:
Membership Inference Attacks on Diffusion Models via Quantile Regression. ICML 2024 - [c11]Shuai Tang, Sergül Aydöre, Michael Kearns, Saeyoung Rho, Aaron Roth, Yichen Wang, Yu-Xiang Wang, Zhiwei Steven Wu:
Improved Differentially Private Regression via Gradient Boosting. SaTML 2024: 33-56 - 2023
- [i16]Shuai Tang, Sergül Aydöre, Michael Kearns, Saeyoung Rho, Aaron Roth, Yichen Wang, Yu-Xiang Wang, Zhiwei Steven Wu:
Improved Differentially Private Regression via Gradient Boosting. CoRR abs/2303.03451 (2023) - [i15]Dionysis Manousakas, Sergül Aydöre:
On the Usefulness of Synthetic Tabular Data Generation. CoRR abs/2306.15636 (2023) - [i14]Haleh Akrami, Omar Zamzam, Anand A. Joshi, Sergül Aydöre, Richard M. Leahy:
Beta quantile regression for robust estimation of uncertainty in the presence of outliers. CoRR abs/2309.07374 (2023) - [i13]Shuai Tang, Zhiwei Steven Wu, Sergül Aydöre, Michael Kearns, Aaron Roth:
Membership Inference Attacks on Diffusion Models via Quantile Regression. CoRR abs/2312.05140 (2023) - 2022
- [j3]Haleh Akrami
, Anand A. Joshi, Jian Li, Sergül Aydöre, Richard M. Leahy:
A robust variational autoencoder using beta divergence. Knowl. Based Syst. 238: 107886 (2022) - [c10]Yigitcan Kaya, Muhammad Bilal Zafar, Sergül Aydöre, Nathalie Rauschmayr, Krishnaram Kenthapadi:
Generating Distributional Adversarial Examples to Evade Statistical Detectors. ICML 2022: 10895-10911 - [c9]Giuseppe Vietri, Cédric Archambeau, Sergül Aydöre, William Brown, Michael Kearns, Aaron Roth, Amaresh Ankit Siva, Shuai Tang, Zhiwei Steven Wu:
Private Synthetic Data for Multitask Learning and Marginal Queries. NeurIPS 2022 - [i12]Giuseppe Vietri, Cédric Archambeau, Sergül Aydöre, William Brown, Michael Kearns, Aaron Roth, Amaresh Ankit Siva, Shuai Tang, Zhiwei Steven Wu:
Private Synthetic Data for Multitask Learning and Marginal Queries. CoRR abs/2209.07400 (2022) - 2021
- [c8]Sergül Aydöre, William Brown, Michael Kearns, Krishnaram Kenthapadi, Luca Melis, Aaron Roth, Amaresh Ankit Siva:
Differentially Private Query Release Through Adaptive Projection. ICML 2021: 457-467 - [c7]Haleh Akrami, Anand A. Joshi, Sergül Aydöre, Richard M. Leahy:
Quantile Regression for Uncertainty Estimation in VAEs with Applications to Brain Lesion Detection. IPMI 2021: 689-700 - [c6]Ecenaz Erdemir, Jeffrey Bickford, Luca Melis, Sergül Aydöre:
Adversarial Robustness with Non-uniform Perturbations. NeurIPS 2021: 19147-19159 - [i11]Ecenaz Erdemir, Jeffrey Bickford, Luca Melis, Sergül Aydöre:
Adversarial Robustness with Non-uniform Perturbations. CoRR abs/2102.12002 (2021) - [i10]Sergül Aydöre, William Brown, Michael Kearns, Krishnaram Kenthapadi, Luca Melis, Aaron Roth, Amaresh Ankit Siva:
Differentially Private Query Release Through Adaptive Projection. CoRR abs/2103.06641 (2021) - [i9]Haleh Akrami, Anand A. Joshi, Sergül Aydöre, Richard M. Leahy:
Deep Quantile Regression for Uncertainty Estimation in Unsupervised and Supervised Lesion Detection. CoRR abs/2109.09374 (2021) - 2020
- [c5]Haleh Akrami, Anand A. Joshi, Jian Li, Sergül Aydöre, Richard M. Leahy:
Brain Lesion Detection Using A Robust Variational Autoencoder and Transfer Learning. ISBI 2020: 786-790 - [i8]Liyan Chen, Philip Gautier, Sergül Aydöre:
DropCluster: A structured dropout for convolutional networks. CoRR abs/2002.02997 (2020) - [i7]Haleh Akrami, Sergül Aydöre, Richard M. Leahy, Anand A. Joshi:
Robust Variational Autoencoder for Tabular Data with Beta Divergence. CoRR abs/2006.08204 (2020) - [i6]Haleh Akrami, Anand A. Joshi, Sergül Aydöre, Richard M. Leahy:
Addressing Variance Shrinkage in Variational Autoencoders using Quantile Regression. CoRR abs/2010.09042 (2020)
2010 – 2019
- 2019
- [c4]Sergül Aydöre, Bertrand Thirion, Gaël Varoquaux:
Feature Grouping as a Stochastic Regularizer for High-Dimensional Structured Data. ICML 2019: 385-394 - [c3]Sergül Aydöre, Tianhao Zhu, Dean P. Foster:
Dynamic Local Regret for Non-convex Online Forecasting. NeurIPS 2019: 7980-7989 - [i5]Tianhao Zhu, Sergül Aydöre:
Time-Smoothed Gradients for Online Forecasting. CoRR abs/1905.08850 (2019) - [i4]Bingyang Wen, Sergül Aydöre:
ROMark: A Robust Watermarking System Using Adversarial Training. CoRR abs/1910.01221 (2019) - [i3]Sergül Aydöre, Tianhao Zhu, Dean P. Foster:
Dynamic Local Regret for Non-convex Online Forecasting. CoRR abs/1910.07927 (2019) - 2018
- [i2]Sergül Aydöre, Bertrand Thirion, Olivier Grisel, Gaël Varoquaux:
Using Feature Grouping as a Stochastic Regularizer for High-Dimensional Noisy Data. CoRR abs/1807.11718 (2018) - [i1]Sergül Aydöre, Lee H. Dicker, Dean P. Foster:
A Local Regret in Nonconvex Online Learning. CoRR abs/1811.05095 (2018) - 2013
- [j2]Sergül Aydöre, Dimitrios Pantazis, Richard M. Leahy:
A note on the phase locking value and its properties. NeuroImage 74: 231-244 (2013) - [c2]Sergül Aydöre, Syed Ashrafulla, Anand A. Joshi, Richard M. Leahy:
A measure of connectivity in the presence of crosstalk. ACSSC 2013: 1848-1852 - 2012
- [c1]Sergül Aydöre, Dimitrios Pantazis, Richard M. Leahy:
Phase synchrony in multivariate Gaussian data with applications to cortical networks. ISBI 2012: 1547-1550 - 2010
- [j1]Sergül Aydöre, Mehmet Kivanç Mihçak, R. Koray Çiftçi, Ata Akin:
On Temporal Connectivity of PFC Via Gauss - Markov Modeling of fNIRS Signals. IEEE Trans. Biomed. Eng. 57(3): 761-768 (2010)
Coauthor Index
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last updated on 2024-09-04 00:31 CEST by the dblp team
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