Mikko A. Heikkilä

According to our database, Mikko A. Heikkilä authored at least 11 papers between 2017 and 2024.

Collaborative distances:

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

2024

On Joint Noise Scaling in Differentially Private Federated Learning with Multiple Local Steps.

Mikko A. Heikkilä

CoRR, 2024

Speech Robust Bench: A Robustness Benchmark For Speech Recognition.

Muhammad A. Shah, David Solans Noguero, Mikko A. Heikkilä, Nicolas Kourtellis

CoRR, 2024

PUFFLE: Balancing Privacy, Utility, and Fairness in Federated Learning.

Luca Corbucci, Mikko A. Heikkilä, David Solans Noguero, Anna Monreale, Nicolas Kourtellis

Proceedings of the ECAI 2024 - 27th European Conference on Artificial Intelligence, 19-24 October 2024, Santiago de Compostela, Spain, 2024

2023

Numerical Accounting in the Shuffle Model of Differential Privacy.

Antti Koskela, Mikko A. Heikkilä, Antti Honkela

Trans. Mach. Learn. Res., 2023

Differentially private partitioned variational inference.

Mikko A. Heikkilä, Matthew Ashman, Siddharth Swaroop, Richard E. Turner, Antti Honkela

Trans. Mach. Learn. Res., 2023

2021

Tight Accounting in the Shuffle Model of Differential Privacy.

Antti Koskela, Mikko A. Heikkilä, Antti Honkela

CoRR, 2021

2020

Differentially private cross-silo federated learning.

Mikko A. Heikkilä, Antti Koskela, Kana Shimizu, Samuel Kaski, Antti Honkela

CoRR, 2020

2019

Representation transfer for differentially private drug sensitivity prediction.

Teppo Mikael Niinimäki, Mikko A. Heikkilä, Antti Honkela, Samuel Kaski

Bioinform., 2019

Differentially Private Markov Chain Monte Carlo.

Mikko A. Heikkilä, Joonas Jälkö, Onur Dikmen, Antti Honkela

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2017

Differentially Private Bayesian Learning on Distributed Data.

Mikko A. Heikkilä, Yusuke Okimoto, Samuel Kaski, Kana Shimizu, Antti Honkela

CoRR, 2017

Differentially private Bayesian learning on distributed data.

Mikko A. Heikkilä, Eemil Lagerspetz, Samuel Kaski, Kana Shimizu, Sasu Tarkoma, Antti Honkela

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017