Joonas Jälkö

According to our database1, Joonas Jälkö authored at least 18 papers between 2017 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Links

On csauthors.net:

Bibliography

2024
Collaborative learning from distributed data with differentially private synthetic data.
BMC Medical Informatics Decis. Mak., December, 2024

Understanding Practical Membership Privacy of Deep Learning.
CoRR, 2024

Subsampling is not Magic: Why Large Batch Sizes Work for Differentially Private Stochastic Optimisation.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Privacy-Aware Document Visual Question Answering.
Proceedings of the Document Analysis and Recognition - ICDAR 2024 - 18th International Conference, Athens, Greece, August 30, 2024

2023
DPVIm: Differentially Private Variational Inference Improved.
Trans. Mach. Learn. Res., 2023

Collaborative Learning From Distributed Data With Differentially Private Synthetic Twin Data.
CoRR, 2023

Noise-Aware Statistical Inference with Differentially Private Synthetic Data.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2021
Privacy-preserving data sharing via probabilistic modeling.
Patterns, 2021

Locally Differentially Private Bayesian Inference.
CoRR, 2021

Differentially Private Bayesian Inference for Generalized Linear Models.
Proceedings of the 38th International Conference on Machine Learning, 2021

Tight Differential Privacy for Discrete-Valued Mechanisms and for the Subsampled Gaussian Mechanism Using FFT.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
Privacy-preserving Data Sharing on Vertically Partitioned Data.
CoRR, 2020

Tight Approximate Differential Privacy for Discrete-Valued Mechanisms Using FFT.
CoRR, 2020

Computing Tight Differential Privacy Guarantees Using FFT.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
Privacy-preserving data sharing via probabilistic modelling.
CoRR, 2019

Computing Exact Guarantees for Differential Privacy.
CoRR, 2019

Differentially Private Markov Chain Monte Carlo.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2017
Differentially Private Variational Inference for Non-conjugate Models.
Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017


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