Differentially private Bayesian learning on distributed data. - Mikko A. Heikkilä; Eemil Lagerspetz; Samuel Kaski; Kana Shimizu; Sasu Tarkoma; Antti Honkela (NIPS, 2017)

Differentially Private Bayesian Learning on Distributed Data. - Mikko A. Heikkilä; Yusuke Okimoto; Samuel Kaski; Kana Shimizu; Antti Honkela (CoRR, 2017)

Differentially Private Markov Chain Monte Carlo. - Mikko A. Heikkilä; Joonas Jälkö; Onur Dikmen; Antti Honkela (NeurIPS, 2019)

Representation transfer for differentially private drug sensitivity prediction. - Teppo Mikael Niinimäki; Mikko A. Heikkilä; Antti Honkela; Samuel Kaski (Bioinform., 2019)

Differentially private cross-silo federated learning. - Mikko A. Heikkilä; Antti Koskela; Kana Shimizu; Samuel Kaski; Antti Honkela (CoRR, 2020)

Tight Accounting in the Shuffle Model of Differential Privacy. - Antti Koskela; Mikko A. Heikkilä; Antti Honkela (CoRR, 2021)

Differentially private partitioned variational inference. - Mikko A. Heikkilä; Matthew Ashman; Siddharth Swaroop; Richard E. Turner; Antti Honkela (Trans. Mach. Learn. Res., 2023)

Numerical Accounting in the Shuffle Model of Differential Privacy. - Antti Koskela; Mikko A. Heikkilä; Antti Honkela (Trans. Mach. Learn. Res., 2023)

PUFFLE: Balancing Privacy, Utility, and Fairness in Federated Learning. - Luca Corbucci; Mikko A. Heikkilä; David Solans Noguero; Anna Monreale; Nicolas Kourtellis (ECAI, 2024)

Speech Robust Bench: A Robustness Benchmark For Speech Recognition. - Muhammad A. Shah; David Solans Noguero; Mikko A. Heikkilä; Nicolas Kourtellis (CoRR, 2024)

On Joint Noise Scaling in Differentially Private Federated Learning with Multiple Local Steps. - Mikko A. Heikkilä (CoRR, 2024)

Non-IID data in Federated Learning: A Survey with Taxonomy, Metrics, Methods, Frameworks and Future Directions. - Daniel Mauricio Jimenez Gutierrez; David Solans; Mikko A. Heikkilä; Andrea Vitaletti; Nicolas Kourtellis; Aris Anagnostopoulos; Ioannis Chatzigiannakis (CoRR, 2024)

Speech Robust Bench: A Robustness Benchmark For Speech Recognition. - Muhammad A. Shah; David Solans Noguero; Mikko A. Heikkilä; Bhiksha Raj; Nicolas Kourtellis (ICLR, 2025)

On Using Secure Aggregation in Differentially Private Federated Learning with Multiple Local Steps. - Mikko A. Heikkilä (Trans. Mach. Learn. Res., 2025)

Mitigating Disparate Impact of Differentially Private Learning through Bounded Adaptive Clipping. - Linzh Zhao; Aki Rehn; Mikko A. Heikkilä; Razane Tajeddine; Antti Honkela (CoRR, 2025)