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ORCIDAli Burak Ünal
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2020 – today
- 2024
[j3]Ali Burak Ünal, Nico Pfeifer, Mete Akgün:
A privacy-preserving approach for cloud-based protein fold recognition. Patterns 5(9): 101023 (2024)- [i12]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) - [i11]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) - [i10]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) - [i9]Anika Hannemann, Arjhun Swaminathan, Ali Burak Ünal, Mete Akgün:
Private, Efficient and Scalable Kernel Learning for Medical Image Analysis. CoRR abs/2410.15840 (2024) - [i8]Seyma Selcan Magara, Noah Dietrich, Ali Burak Ünal, Mete Akgün:
Accelerating Privacy-Preserving Medical Record Linkage: A Three-Party MPC Approach. CoRR abs/2410.21605 (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 2024-12-01 01:06 CET by the dblp team
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