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ORCIDMikko A. Heikkilä
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2020 – today
- 2024
[c3]Luca Corbucci, Mikko A. Heikkilä, David Solans Noguero, Anna Monreale, Nicolas Kourtellis:
PUFFLE: Balancing Privacy, Utility, and Fairness in Federated Learning. ECAI 2024: 1639-1647- [i9]Muhammad A. Shah, David Solans Noguero, Mikko A. Heikkilä, Nicolas Kourtellis:
Speech Robust Bench: A Robustness Benchmark For Speech Recognition. CoRR abs/2403.07937 (2024) - [i8]Luca Corbucci, Mikko A. Heikkilä, David Solans Noguero, Anna Monreale, Nicolas Kourtellis:
PUFFLE: Balancing Privacy, Utility, and Fairness in Federated Learning. CoRR abs/2407.15224 (2024) - [i7]Mikko A. Heikkilä:
On Joint Noise Scaling in Differentially Private Federated Learning with Multiple Local Steps. CoRR abs/2407.19286 (2024) - 2023
- [j3]Mikko A. Heikkilä, Matthew Ashman, Siddharth Swaroop, Richard E. Turner, Antti Honkela:
Differentially private partitioned variational inference. Trans. Mach. Learn. Res. 2023 (2023) - [j2]Antti Koskela, Mikko A. Heikkilä, Antti Honkela:
Numerical Accounting in the Shuffle Model of Differential Privacy. Trans. Mach. Learn. Res. 2023 (2023) - 2022
- [i6]Mikko A. Heikkilä
, Matthew Ashman, Siddharth Swaroop, Richard E. Turner, Antti Honkela:
Differentially private partitioned variational inference. CoRR abs/2209.11595 (2022) - 2021
- [i5]Antti Koskela, Mikko A. Heikkilä, Antti Honkela:
Tight Accounting in the Shuffle Model of Differential Privacy. CoRR abs/2106.00477 (2021) - 2020
- [i4]Mikko A. Heikkilä, Antti Koskela, Kana Shimizu, Samuel Kaski, Antti Honkela:
Differentially private cross-silo federated learning. CoRR abs/2007.05553 (2020)
2010 – 2019
- 2019
- [j1]Teppo Mikael Niinimäki, Mikko A. Heikkilä, Antti Honkela, Samuel Kaski:
Representation transfer for differentially private drug sensitivity prediction. Bioinform. 35(14): i218-i224 (2019) - [c2]Mikko A. Heikkilä, Joonas Jälkö, Onur Dikmen, Antti Honkela:
Differentially Private Markov Chain Monte Carlo. NeurIPS 2019: 4115-4125 - [i3]Teppo Mikael Niinimäki, Mikko A. Heikkilä, Antti Honkela, Samuel Kaski:
Representation Transfer for Differentially Private Drug Sensitivity Prediction. CoRR abs/1901.10227 (2019) - [i2]Mikko A. Heikkilä, Joonas Jälkö, Onur Dikmen, Antti Honkela:
Differentially Private Markov Chain Monte Carlo. CoRR abs/1901.10275 (2019) - 2017
- [c1]Mikko A. Heikkilä, Eemil Lagerspetz, Samuel Kaski, Kana Shimizu, Sasu Tarkoma, Antti Honkela:
Differentially private Bayesian learning on distributed data. NIPS 2017: 3226-3235 - [i1]Mikko A. Heikkilä, Yusuke Okimoto, Samuel Kaski, Kana Shimizu, Antti Honkela:
Differentially Private Bayesian Learning on Distributed Data. CoRR abs/1703.01106 (2017)
Coauthor Index
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