Ali Burak Ünal

Orcid: 0000-0002-7279-620X

According to our database1, Ali Burak Ünal authored at least 25 papers between 2016 and 2025.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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In proceedings 
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PhD thesis 
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Links

On csauthors.net:

Bibliography

2025
Accurate and Private Diagnosis of Rare Genetic Syndromes from Facial Images with Federated Deep Learning.
CoRR, September, 2025

Federated Learning for Epileptic Seizure Prediction Across Heterogeneous EEG Datasets.
CoRR, August, 2025

Accelerating probabilistic privacy-preserving medical record linkage: A three-party MPC approach.
J. Biomed. Informatics, 2025

Privacy-preserving federated unsupervised domain adaptation with application to age prediction from DNA methylation data.
Bioinform., 2025

Robust Representation Learning for Privacy-Preserving Machine Learning: A Multi-Objective Autoencoder Approach.
IEEE Access, 2025

Secure and Efficient Logistic Regression With Secret-Sharing MPC and Differential Privacy.
IEEE Access, 2025

2024
A privacy-preserving approach for cloud-based protein fold recognition.
Patterns, 2024

Accelerating Privacy-Preserving Medical Record Linkage: A Three-Party MPC Approach.
CoRR, 2024

PP-GWAS: Privacy Preserving Multi-Site Genome-wide Association Studies.
CoRR, 2024

FHAUC: Privacy Preserving AUC Calculation for Federated Learning using Fully Homomorphic Encryption.
CoRR, 2024

Privacy Preserving Data Imputation via Multi-Party Computation for Medical Applications.
Proceedings of the IEEE International Conference on E-health Networking, 2024

Private, Efficient and Scalable Kernel Learning for Medical Image Analysis.
Proceedings of the Computational Intelligence Methods for Bioinformatics and Biostatistics, 2024

2023
A Privacy-Preserving Federated Learning Approach for Kernel methods.
CoRR, 2023

A Privacy-Preserving Framework for Collaborative Machine Learning with Kernel Methods.
Proceedings of the 5th IEEE International Conference on Trust, 2023

ppAURORA: Privacy Preserving Area Under Receiver Operating Characteristic and Precision-Recall Curves.
Proceedings of the Network and System Security - 17th International Conference, 2023

2022
Towards a Complete Privacy Preserving Machine Learning Pipeline.
PhD thesis, 2022

CECILIA: Comprehensive Secure Machine Learning Framework.
CoRR, 2022

2021
ppAUC: Privacy Preserving Area Under the Curve with Secure 3-Party Computation.
CoRR, 2021

PAMOGK: a pathway graph kernel-based multiomics approach for patient clustering.
Bioinform., 2021

Identifying disease-causing mutations with privacy protection.
Bioinform., 2021

ESCAPED: Efficient Secure and Private Dot Product Framework for Kernel-based Machine Learning Algorithms with Applications in Healthcare.
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.
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.
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.
Proceedings of the Cryptology and Network Security - 18th International Conference, 2019

2016
Identification of Cancer Patient Subgroups via Smoothed Shortest Path Graph Kernel.
CoRR, 2016


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