Sergül Aydöre

36 papers A* 8Misc 2Journal 21Unranked 5

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	Auto-GDA: Automatic Domain Adaptation for Efficient Grounding Verification in Retrieval-Augmented Generation. ICLR Tobias Leemann, Periklis Petridis, Giuseppe Vietri, Dionysis Manousakas, Aaron Roth, Sergül Aydöre
2025	—	`conf`	Benchmarking Query-Conditioned Natural Language Inference. ACL (Findings) Marc E. Canby, Xinchi Chen, Xing Niu, Jifan Chen, Bonan Min, Sergül Aydöre, Vittorio Castelli
2024	J	`jnl`	Auto-GDA: Automatic Domain Adaptation for Efficient Grounding Verification in Retrieval Augmented Generation. CoRR Tobias Leemann, Periklis Petridis, Giuseppe Vietri, Dionysis Manousakas, Aaron Roth, Sergül Aydöre
2024	Misc	`conf`	Beta Quantile Regression for Robust Estimation of Uncertainty in the Presence of Outliers. ICASSP Haleh Akrami, Omar Zamzam, Anand A. Joshi, Sergül Aydöre, Richard M. Leahy
2024	—	`conf`	Improved Differentially Private Regression via Gradient Boosting. SaTML Shuai Tang, Sergül Aydöre, Michael Kearns, Saeyoung Rho, Aaron Roth, Yichen Wang, Yu-Xiang Wang, Zhiwei Steven Wu
2024	J	`jnl`	Language-Model Prior Overcomes Cold-Start Items. CoRR Shiyu Wang, Hao Ding, Yupeng Gu, Sergül Aydöre, Kousha Kalantari, Branislav Kveton
2024	A*	`conf`	Membership Inference Attacks on Diffusion Models via Quantile Regression. ICML Shuai Tang, Steven Wu, Sergül Aydöre, Michael Kearns, Aaron Roth
2023	J	`jnl`	Beta quantile regression for robust estimation of uncertainty in the presence of outliers. CoRR Haleh Akrami, Omar Zamzam, Anand A. Joshi, Sergül Aydöre, Richard M. Leahy
2023	J	`jnl`	Improved Differentially Private Regression via Gradient Boosting. CoRR Shuai Tang, Sergül Aydöre, Michael Kearns, Saeyoung Rho, Aaron Roth, Yichen Wang, Yu-Xiang Wang, Zhiwei Steven Wu
2023	J	`jnl`	Membership Inference Attacks on Diffusion Models via Quantile Regression. CoRR Shuai Tang, Zhiwei Steven Wu, Sergül Aydöre, Michael Kearns, Aaron Roth
2023	J	`jnl`	On the Usefulness of Synthetic Tabular Data Generation. CoRR Dionysis Manousakas, Sergül Aydöre
2022	J	`jnl`	A robust variational autoencoder using beta divergence. Knowl. Based Syst. Haleh Akrami, Anand A. Joshi, Jian Li, Sergül Aydöre, Richard M. Leahy
2022	A*	`conf`	Generating Distributional Adversarial Examples to Evade Statistical Detectors. ICML Yigitcan Kaya, Muhammad Bilal Zafar, Sergül Aydöre, Nathalie Rauschmayr, Krishnaram Kenthapadi
2022	A*	`conf`	Private Synthetic Data for Multitask Learning and Marginal Queries. NeurIPS Giuseppe Vietri, Cédric Archambeau, Sergül Aydöre, William Brown, Michael Kearns, Aaron Roth, Amaresh Ankit Siva, Shuai Tang, Zhiwei Steven Wu
2022	J	`jnl`	Private Synthetic Data for Multitask Learning and Marginal Queries. CoRR Giuseppe Vietri, Cédric Archambeau, Sergül Aydöre, William Brown, Michael Kearns, Aaron Roth, Amaresh Ankit Siva, Shuai Tang, Zhiwei Steven Wu
2021	A*	`conf`	Adversarial Robustness with Non-uniform Perturbations. NeurIPS Ecenaz Erdemir, Jeffrey Bickford, Luca Melis, Sergül Aydöre
2021	J	`jnl`	Adversarial Robustness with Non-uniform Perturbations. CoRR Ecenaz Erdemir, Jeffrey Bickford, Luca Melis, Sergül Aydöre
2021	J	`jnl`	Deep Quantile Regression for Uncertainty Estimation in Unsupervised and Supervised Lesion Detection. CoRR Haleh Akrami, Anand A. Joshi, Sergül Aydöre, Richard M. Leahy
2021	A*	`conf`	Differentially Private Query Release Through Adaptive Projection. ICML Sergül Aydöre, William Brown, Michael Kearns, Krishnaram Kenthapadi, Luca Melis, Aaron Roth, Amaresh Ankit Siva
2021	J	`jnl`	Differentially Private Query Release Through Adaptive Projection. CoRR Sergül Aydöre, William Brown, Michael Kearns, Krishnaram Kenthapadi, Luca Melis, Aaron Roth, Amaresh Ankit Siva
2021	—	`conf`	Quantile Regression for Uncertainty Estimation in VAEs with Applications to Brain Lesion Detection. IPMI Haleh Akrami, Anand A. Joshi, Sergül Aydöre, Richard M. Leahy
2020	J	`jnl`	Addressing Variance Shrinkage in Variational Autoencoders using Quantile Regression. CoRR Haleh Akrami, Anand A. Joshi, Sergül Aydöre, Richard M. Leahy
2020	—	`conf`	Brain Lesion Detection Using A Robust Variational Autoencoder and Transfer Learning. ISBI Haleh Akrami, Anand A. Joshi, Jian Li, Sergül Aydöre, Richard M. Leahy
2020	J	`jnl`	DropCluster: A structured dropout for convolutional networks. CoRR Liyan Chen, Philip Gautier, Sergül Aydöre
2020	J	`jnl`	Robust Variational Autoencoder for Tabular Data with Beta Divergence. CoRR Haleh Akrami, Sergül Aydöre, Richard M. Leahy, Anand A. Joshi
2019	A*	`conf`	Dynamic Local Regret for Non-convex Online Forecasting. NeurIPS Sergül Aydöre, Tianhao Zhu, Dean P. Foster
2019	J	`jnl`	Dynamic Local Regret for Non-convex Online Forecasting. CoRR Sergül Aydöre, Tianhao Zhu, Dean P. Foster
2019	A*	`conf`	Feature Grouping as a Stochastic Regularizer for High-Dimensional Structured Data. ICML Sergül Aydöre, Bertrand Thirion, Gaël Varoquaux
2019	J	`jnl`	ROMark: A Robust Watermarking System Using Adversarial Training. CoRR Bingyang Wen, Sergül Aydöre
2019	J	`jnl`	Time-Smoothed Gradients for Online Forecasting. CoRR Tianhao Zhu, Sergül Aydöre
2018	J	`jnl`	A Local Regret in Nonconvex Online Learning. CoRR Sergül Aydöre, Lee H. Dicker, Dean P. Foster
2018	J	`jnl`	Using Feature Grouping as a Stochastic Regularizer for High-Dimensional Noisy Data. CoRR Sergül Aydöre, Bertrand Thirion, Olivier Grisel, Gaël Varoquaux
2013	Misc	`conf`	A measure of connectivity in the presence of crosstalk. ACSSC Sergül Aydöre, Syed Ashrafulla, Anand A. Joshi, Richard M. Leahy
2013	J	`jnl`	A note on the phase locking value and its properties. NeuroImage Sergül Aydöre, Dimitrios Pantazis, Richard M. Leahy
2012	—	`conf`	Phase synchrony in multivariate Gaussian data with applications to cortical networks. ISBI Sergül Aydöre, Dimitrios Pantazis, Richard M. Leahy
2010	J	`jnl`	On Temporal Connectivity of PFC Via Gauss - Markov Modeling of fNIRS Signals. IEEE Trans. Biomed. Eng. Sergül Aydöre, Mehmet Kivanç Mihçak, R. Koray Çiftçi, Ata Akin