| Differentially private bayesian learning on distributed data M Heikkilä, E Lagerspetz, S Kaski, K Shimizu, S Tarkoma, A Honkela Advances in neural information processing systems 30, 2017 | 69 | 2017 |
| Differentially private cross-silo federated learning MA Heikkilä, A Koskela, K Shimizu, S Kaski, A Honkela arXiv preprint arXiv:2007.05553, 2020 | 37 | 2020 |
| Differentially private markov chain monte carlo M Heikkilä, J Jälkö, O Dikmen, A Honkela Advances in Neural Information Processing Systems 32, 2019 | 33 | 2019 |
| Tight accounting in the shuffle model of differential privacy A Koskela, MA Heikkilä, A Honkela arXiv preprint arXiv:2106.00477, 2021 | 17 | 2021 |
| Representation transfer for differentially private drug sensitivity prediction T Niinimäki, MA Heikkilä, A Honkela, S Kaski Bioinformatics 35 (14), i218-i224, 2019 | 13 | 2019 |
| Numerical accounting in the shuffle model of differential privacy A Koskela, M Heikkilä, A Honkela Transactions on machine learning research, 2023 | 8 | 2023 |
| Speech robust bench: a robustness benchmark for speech recognition MA Shah, DS Noguero, MA Heikkila, B Raj, N Kourtellis arXiv preprint arXiv:2403.07937, 2024 | 4 | 2024 |
| Non-IID data in Federated Learning: A Survey with Taxonomy, Metrics, Methods, Frameworks and Future Directions D Solans, M Heikkila, A Vitaletti, N Kourtellis, A Anagnostopoulos, ... arXiv preprint arXiv:2411.12377, 2024 | 3 | 2024 |
| PUFFLE: Balancing Privacy, Utility, and Fairness in Federated Learning L Corbucci, MA Heikkila, DS Noguero, A Monreale, N Kourtellis arXiv preprint arXiv:2407.15224, 2024 | 3 | 2024 |
| Performanssiteorian tulkinta suomalaisessa folkloristiikassa M Heikkilä Folkloristiikan pro gradu-tutkielma. Helsingin yliopisto, 2013 | 2 | 2013 |
| On Joint Noise Scaling in Differentially Private Federated Learning with Multiple Local Steps MA Heikkilä arXiv preprint arXiv:2407.19286, 2024 | 1 | 2024 |
| Differentially private partitioned variational inference MA Heikkilä, M Ashman, S Swaroop, RE Turner, A Honkela arXiv preprint arXiv:2209.11595, 2022 | 1 | 2022 |
| Non-IID data in Federated Learning: A Systematic Review with Taxonomy, Metrics, Methods, Frameworks and Future Directions DM Jimenez G, D Solans, M Heikkila, A Vitaletti, N Kourtellis, ... arXiv e-prints, arXiv: 2411.12377, 2024 | | 2024 |
| Differentially private and distributed Bayesian learning M Heikkilä Helsingin yliopisto, 2023 | | 2023 |
| Deep Transfer Learning of Representations for Differentially Private Learning T Niinimäki, MA Heikkilä, S Kaski, A Honkela Federated Artificial Intelligence Meeting Workshop, 2018 | | 2018 |
| Quasi-Pseudolikelihood in Markov network structure learning M Heikkilä Helsingfors universitet, 2016 | | 2016 |
| Supplement to “Differentially private Bayesian learning on distributed data” M Heikkilä, E Lagerspetz, S Kaski, K Shimizu, S Tarkoma, A Honkela | | |
| Efficient Privacy-Preserving Machine Learning M Das, O Dikmen, M Heikkilä, A Honkela, J Jälkö, S Kaski, Y Lu, ... | | |
Antti HonkelaProfessor, University of Helsinki確認したメール アドレス: helsinki.fi
