Mikko A. Heikkilä

20 papers A* 2A 1Journal 16Unranked 1
YearRankTypeTitle / Venue / Authors
2025 J jnl
Mitigating Disparate Impact of Differentially Private Learning through Bounded Adaptive Clipping.
CoRR
Linzh Zhao, Aki Rehn, Mikko A. Heikkilä, Razane Tajeddine, Antti Honkela
2025 J jnl
On Optimal Hyperparameters for Differentially Private Deep Transfer Learning.
CoRR
Aki Rehn, Linzh Zhao, Mikko A. Heikkilä, Antti Honkela
2025 J jnl
On Using Secure Aggregation in Differentially Private Federated Learning with Multiple Local Steps.
Trans. Mach. Learn. Res.
Mikko A. Heikkilä
2025 A* conf
Speech Robust Bench: A Robustness Benchmark For Speech Recognition.
ICLR
Muhammad A. Shah, David Solans Noguero, Mikko A. Heikkilä, Bhiksha Raj, Nicolas Kourtellis
2024 J jnl
Non-IID data in Federated Learning: A Survey with Taxonomy, Metrics, Methods, Frameworks and Future Directions.
CoRR
Daniel Mauricio Jimenez Gutierrez, David Solans, Mikko A. Heikkilä, Andrea Vitaletti, Nicolas Kourtellis, Aris Anagnostopoulos, Ioannis Chatzigiannakis
2024 J jnl
On Joint Noise Scaling in Differentially Private Federated Learning with Multiple Local Steps.
CoRR
Mikko A. Heikkilä
2024 A conf
PUFFLE: Balancing Privacy, Utility, and Fairness in Federated Learning.
ECAI
Luca Corbucci, Mikko A. Heikkilä, David Solans Noguero, Anna Monreale, Nicolas Kourtellis
2024 J jnl
PUFFLE: Balancing Privacy, Utility, and Fairness in Federated Learning.
CoRR
Luca Corbucci, Mikko A. Heikkilä, David Solans Noguero, Anna Monreale, Nicolas Kourtellis
2024 J jnl
Speech Robust Bench: A Robustness Benchmark For Speech Recognition.
CoRR
Muhammad A. Shah, David Solans Noguero, Mikko A. Heikkilä, Nicolas Kourtellis
2023 J jnl
Differentially private partitioned variational inference.
Trans. Mach. Learn. Res.
Mikko A. Heikkilä, Matthew Ashman, Siddharth Swaroop, Richard E. Turner, Antti Honkela
2023 J jnl
Numerical Accounting in the Shuffle Model of Differential Privacy.
Trans. Mach. Learn. Res.
Antti Koskela, Mikko A. Heikkilä, Antti Honkela
2022 J jnl
Differentially private partitioned variational inference.
CoRR
Mikko A. Heikkilä, Matthew Ashman, Siddharth Swaroop, Richard E. Turner, Antti Honkela
2021 J jnl
Tight Accounting in the Shuffle Model of Differential Privacy.
CoRR
Antti Koskela, Mikko A. Heikkilä, Antti Honkela
2020 J jnl
Differentially private cross-silo federated learning.
CoRR
Mikko A. Heikkilä, Antti Koskela, Kana Shimizu, Samuel Kaski, Antti Honkela
2019 A* conf
Differentially Private Markov Chain Monte Carlo.
NeurIPS
Mikko A. Heikkilä, Joonas Jälkö, Onur Dikmen, Antti Honkela
2019 J jnl
Differentially Private Markov Chain Monte Carlo.
CoRR
Mikko A. Heikkilä, Joonas Jälkö, Onur Dikmen, Antti Honkela
2019 J jnl
Representation Transfer for Differentially Private Drug Sensitivity Prediction.
CoRR
Teppo Mikael Niinimäki, Mikko A. Heikkilä, Antti Honkela, Samuel Kaski
2019 J jnl
Representation transfer for differentially private drug sensitivity prediction.
Bioinform.
Teppo Mikael Niinimäki, Mikko A. Heikkilä, Antti Honkela, Samuel Kaski
2017 J jnl
Differentially Private Bayesian Learning on Distributed Data.
CoRR
Mikko A. Heikkilä, Yusuke Okimoto, Samuel Kaski, Kana Shimizu, Antti Honkela
2017 — conf
Differentially private Bayesian learning on distributed data.
NIPS
Mikko A. Heikkilä, Eemil Lagerspetz, Samuel Kaski, Kana Shimizu, Sasu Tarkoma, Antti Honkela