Ali Burak Ünal

According to our database, Ali Burak Ünal authored at least 23 papers between 2016 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Federated Learning for Epileptic Seizure Prediction Across Heterogeneous EEG Datasets.

Cem Ata Baykara, Saurav Raj Pandey, Ali Burak Ünal, Harlin Lee, Mete Akgün

CoRR, August, 2025

Secure and Efficient Logistic Regression With Secret-Sharing MPC and Differential Privacy.

Seyma Selcan Magara, Ipek Motorcu, Emin Sahin Mektepli, Cem Ata Baykara, Ali Burak Ünal, Mete Akgün

IEEE Access, 2025

2024

A privacy-preserving approach for cloud-based protein fold recognition.

Ali Burak Ünal, Nico Pfeifer, Mete Akgün

Patterns, 2024

Privacy Preserving Federated Unsupervised Domain Adaptation with Application to Age Prediction from DNA Methylation Data.

Cem Ata Baykara, Ali Burak Ünal, Nico Pfeifer, Mete Akgün

CoRR, 2024

Accelerating Privacy-Preserving Medical Record Linkage: A Three-Party MPC Approach.

Seyma Selcan Magara, Noah Dietrich, Ali Burak Ünal, Mete Akgün

CoRR, 2024

PP-GWAS: Privacy Preserving Multi-Site Genome-wide Association Studies.

Arjhun Swaminathan, Anika Hannemann, Ali Burak Ünal, Nico Pfeifer, Mete Akgün

CoRR, 2024

FHAUC: Privacy Preserving AUC Calculation for Federated Learning using Fully Homomorphic Encryption.

Cem Ata Baykara, Ali Burak Ünal, Mete Akgün

CoRR, 2024

Privacy Preserving Data Imputation via Multi-Party Computation for Medical Applications.

Julia Jentsch, Ali Burak Ünal, Seyma Selcan Magara, Mete Akgün

Proceedings of the IEEE International Conference on E-health Networking, 2024

Private, Efficient and Scalable Kernel Learning for Medical Image Analysis.

Anika Hannemann, Arjhun Swaminathan, Ali Burak Ünal, Mete Akgün

Proceedings of the Computational Intelligence Methods for Bioinformatics and Biostatistics, 2024

2023

Robust Representation Learning for Privacy-Preserving Machine Learning: A Multi-Objective Autoencoder Approach.

Sofiane Ouaari, Ali Burak Ünal, Mete Akgün, Nico Pfeifer

CoRR, 2023

A Privacy-Preserving Federated Learning Approach for Kernel methods.

Anika Hannemann, Ali Burak Ünal, Arjhun Swaminathan, Erik Buchmann, Mete Akgün

CoRR, 2023

A Privacy-Preserving Framework for Collaborative Machine Learning with Kernel Methods.

Anika Hannemann, Ali Burak Ünal, Arjhun Swaminathan, Erik Buchmann, Mete Akgün

Proceedings of the 5th IEEE International Conference on Trust, 2023

ppAURORA: Privacy Preserving Area Under Receiver Operating Characteristic and Precision-Recall Curves.

Ali Burak Ünal, Nico Pfeifer, Mete Akgün

Proceedings of the Network and System Security - 17th International Conference, 2023

2022

Towards a Complete Privacy Preserving Machine Learning Pipeline.

Ali Burak Ünal

PhD thesis, 2022

CECILIA: Comprehensive Secure Machine Learning Framework.

Ali Burak Ünal, Mete Akgün, Nico Pfeifer

CoRR, 2022

2021

ppAUC: Privacy Preserving Area Under the Curve with Secure 3-Party Computation.

Ali Burak Ünal, Nico Pfeifer, Mete Akgün

CoRR, 2021

PAMOGK: a pathway graph kernel-based multiomics approach for patient clustering.

Yasin Ilkagan Tepeli, Ali Burak Ünal, Furkan Mustafa Akdemir, Öznur Tastan

Bioinform., 2021

Identifying disease-causing mutations with privacy protection.

Mete Akgün, Ali Burak Ünal, Bekir Ergüner, Nico Pfeifer, Oliver Kohlbacher

Bioinform., 2021

ESCAPED: Efficient Secure and Private Dot Product Framework for Kernel-based Machine Learning Algorithms with Applications in Healthcare.

Ali Burak Ünal, Mete Akgün, Nico Pfeifer

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Privacy Preserving Gaze Estimation using Synthetic Images via a Randomized Encoding Based Framework.

Efe Bozkir, Ali Burak Ünal, Mete Akgün, Enkelejda Kasneci, Nico Pfeifer

Proceedings of the ETRA '20: 2020 Symposium on Eye Tracking Research and Applications, 2020

Privacy-preserving SVM on Outsourced Genomic Data via Secure Multi-party Computation.

Huajie Chen, Ali Burak Ünal, Mete Akgün, Nico Pfeifer

Proceedings of the IWSPA@CODASPY '20: Proceedings ofthe Sixth International Workshop on Security and Privacy Analytics, 2020

2019

A Framework with Randomized Encoding for a Fast Privacy Preserving Calculation of Non-linear Kernels for Machine Learning Applications in Precision Medicine.

Ali Burak Ünal, Mete Akgün, Nico Pfeifer

Proceedings of the Cryptology and Network Security - 18th International Conference, 2019

2016

Identification of Cancer Patient Subgroups via Smoothed Shortest Path Graph Kernel.

Ali Burak Ünal, Öznur Tastan

CoRR, 2016