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Ali Burak Ünal
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2020 – today
- 2025
[j7]Seyma Selcan Magara
, Ipek Motorcu, Emin Sahin Mektepli, Cem Ata Baykara, Ali Burak Ünal
, Mete Akgün:
Secure and Efficient Logistic Regression With Secret-Sharing MPC and Differential Privacy. IEEE Access 13: 144479-144491 (2025)
[j6]Sofiane Ouaari
, Ali Burak Ünal
, Mete Akgün
, Nico Pfeifer
:
Robust Representation Learning for Privacy-Preserving Machine Learning: A Multi-Objective Autoencoder Approach. IEEE Access 13: 151527-151537 (2025)
[j5]Cem Ata Baykara
, Ali Burak Ünal
, Nico Pfeifer
, Mete Akgün
:
Privacy-preserving federated unsupervised domain adaptation with application to age prediction from DNA methylation data. Bioinform. 41(10) (2025)
[j4]Seyma Selcan Magara
, Noah J. M. Dietrich
, Ali Burak Ünal, Mete Akgün:
Accelerating probabilistic privacy-preserving medical record linkage: A three-party MPC approach. J. Biomed. Informatics 171: 104920 (2025)
[c9]Cem Ata Baykara, Ali Burak Ünal, Mete Akgün:
Enabling Privacy-Preserving Model Evaluation in Federated Learning via Fully Homomorphic Encryption. TPS-ISA 2025: 1-10
[i16]Cem Ata Baykara, Saurav Raj Pandey, Ali Burak Ünal, Harlin Lee, Mete Akgün:
Federated Learning for Epileptic Seizure Prediction Across Heterogeneous EEG Datasets. CoRR abs/2508.08159 (2025)
[i15]Ali Burak Ünal, Cem Ata Baykara, Peter Krawitz, Mete Akgün:
Accurate and Private Diagnosis of Rare Genetic Syndromes from Facial Images with Federated Deep Learning. CoRR abs/2509.10635 (2025)
[i14]Larissa Reichart, Cem Ata Baykara, Ali Burak Ünal, Harlin Lee, Mete Akgün:
Unsupervised Multi-Source Federated Domain Adaptation under Domain Diversity through Group-Wise Discrepancy Minimization. CoRR abs/2510.08150 (2025)- 2024
[j3]Ali Burak Ünal, Nico Pfeifer, Mete Akgün:
A privacy-preserving approach for cloud-based protein fold recognition. Patterns 5(9): 101023 (2024)
[c8]Anika Hannemann, Arjhun Swaminathan
, Ali Burak Ünal, Mete Akgün:
Private, Efficient and Scalable Kernel Learning for Medical Image Analysis. CIBB 2024: 81-95
[c7]Julia Jentsch, Ali Burak Ünal, Seyma Selcan Magara, Mete Akgün:
Privacy Preserving Data Imputation via Multi-Party Computation for Medical Applications. HealthCom 2024: 1-6
[i13]Cem Ata Baykara, Ali Burak Ünal, Mete Akgün:
FHAUC: Privacy Preserving AUC Calculation for Federated Learning using Fully Homomorphic Encryption. CoRR abs/2403.14428 (2024)
[i12]Julia Jentsch, Ali Burak Ünal, Seyma Selcan Magara, Mete Akgün:
Privacy Preserving Data Imputation via Multi-party Computation for Medical Applications. CoRR abs/2405.18878 (2024)
[i11]Arjhun Swaminathan, Anika Hannemann, Ali Burak Ünal, Nico Pfeifer, Mete Akgün:
PP-GWAS: Privacy Preserving Multi-Site Genome-wide Association Studies. CoRR abs/2410.08122 (2024)
[i10]Anika Hannemann, Arjhun Swaminathan, Ali Burak Ünal, Mete Akgün:
Private, Efficient and Scalable Kernel Learning for Medical Image Analysis. CoRR abs/2410.15840 (2024)
[i9]Seyma Selcan Magara, Noah J. M. Dietrich, Ali Burak Ünal, Mete Akgün:
Accelerating Privacy-Preserving Medical Record Linkage: A Three-Party MPC Approach. CoRR abs/2410.21605 (2024)
[i8]Cem Ata Baykara, Ali Burak Ünal, Nico Pfeifer, Mete Akgün:
Privacy Preserving Federated Unsupervised Domain Adaptation with Application to Age Prediction from DNA Methylation Data. CoRR abs/2411.17287 (2024)- 2023
[c6]Ali Burak Ünal
, Nico Pfeifer
, Mete Akgün
:
ppAURORA: Privacy Preserving Area Under Receiver Operating Characteristic and Precision-Recall Curves. NSS 2023: 265-280
[c5]Anika Hannemann
, Ali Burak Ünal, Arjhun Swaminathan
, Erik Buchmann, Mete Akgün:
A Privacy-Preserving Framework for Collaborative Machine Learning with Kernel Methods. TPS-ISA 2023: 82-90
[i7]Anika Hannemann, Ali Burak Ünal, Arjhun Swaminathan, Erik Buchmann, Mete Akgün:
A Privacy-Preserving Federated Learning Approach for Kernel methods. CoRR abs/2306.02677 (2023)
[i6]Sofiane Ouaari, Ali Burak Ünal, Mete Akgün, Nico Pfeifer:
Robust Representation Learning for Privacy-Preserving Machine Learning: A Multi-Objective Autoencoder Approach. CoRR abs/2309.04427 (2023)- 2022
[b1]Ali Burak Ünal:
Towards a Complete Privacy Preserving Machine Learning Pipeline. University of Tübingen, Germany, 2022
[i5]Ali Burak Ünal, Mete Akgün, Nico Pfeifer:
CECILIA: Comprehensive Secure Machine Learning Framework. CoRR abs/2202.03023 (2022)- 2021
[j2]Mete Akgün, Ali Burak Ünal, Bekir Ergüner, Nico Pfeifer
, Oliver Kohlbacher
:
Identifying disease-causing mutations with privacy protection. Bioinform. 36(21): 5205-5213 (2021)
[j1]Yasin Ilkagan Tepeli, Ali Burak Ünal, Furkan Mustafa Akdemir, Öznur Tastan
:
PAMOGK: a pathway graph kernel-based multiomics approach for patient clustering. Bioinform. 36(21): 5237-5246 (2021)
[c4]Ali Burak Ünal, Mete Akgün, Nico Pfeifer:
ESCAPED: Efficient Secure and Private Dot Product Framework for Kernel-based Machine Learning Algorithms with Applications in Healthcare. AAAI 2021: 9988-9996
[i4]Ali Burak Ünal, Nico Pfeifer, Mete Akgün:
ppAUC: Privacy Preserving Area Under the Curve with Secure 3-Party Computation. CoRR abs/2102.08788 (2021)- 2020
[c3]Huajie Chen
, Ali Burak Ünal, Mete Akgün, Nico Pfeifer
:
Privacy-preserving SVM on Outsourced Genomic Data via Secure Multi-party Computation. IWSPA@CODASPY 2020: 61-69
[c2]Efe Bozkir
, Ali Burak Ünal, Mete Akgün, Enkelejda Kasneci, Nico Pfeifer
:
Privacy Preserving Gaze Estimation using Synthetic Images via a Randomized Encoding Based Framework. ETRA Short Papers 2020: 21:1-21:5
[i3]Ali Burak Ünal, Mete Akgün, Nico Pfeifer:
ESCAPED: Efficient Secure and Private Dot Product Framework for Kernel-based Machine Learning Algorithms with Applications in Healthcare. CoRR abs/2012.02688 (2020)
2010 – 2019
- 2019
[c1]Ali Burak Ünal, Mete Akgün, Nico Pfeifer
:
A Framework with Randomized Encoding for a Fast Privacy Preserving Calculation of Non-linear Kernels for Machine Learning Applications in Precision Medicine. CANS 2019: 493-511
[i2]Efe Bozkir, Ali Burak Ünal, Mete Akgün, Enkelejda Kasneci, Nico Pfeifer:
Privacy Preserving Gaze Estimation using Synthetic Images via a Randomized Encoding Based Framework. CoRR abs/1911.07936 (2019)- 2016
[i1]Ali Burak Ünal, Öznur Tastan:
Identification of Cancer Patient Subgroups via Smoothed Shortest Path Graph Kernel. CoRR abs/1612.04431 (2016)
Coauthor Index

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last updated on 2026-03-27 21:00 CET by the dblp team
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