Heikkilä, Ashman, Swaroop, Turner & Honkela 2023:
Differentially private partitioned variational inference. In TMLR.
Koskela, Heikkilä & Honkela 2023:
Numerical accounting in the shuffle model of differential privacy. In TMLR (Featured certification).
Heikkilä, Koskela, Shimizu, Kaski & Honkela 2020:
Differentially private cross-silo federated learning. On ArXiv.
Heikkilä, Jälkö, Dikmen & Honkela 2019:
Differentially private Markov chain Monte Carlo.
In NeurIPS ‘19 (Spotlight).
Niinimäki, Heikkilä, Honkela & Kaski 2019:
Representation transfer for differentially private drug sensitivity prediction.
In ISMB ‘19.
Heikkilä, Lagerspetz, Kaski, Shimizu, Tarkoma & Honkela 2017:
Differentially private Bayesian learning on distributed data.
In NeurIPS ‘17.
Dissertation
My PhD thesis “Differentially private and distributed Bayesian learning” has been accepted with distinction.