Jälkö, Joonas

16 publications

NeurIPS 2025 Impact of Dataset Properties on Membership Inference Vulnerability of Deep Transfer Learning Marlon Tobaben, Hibiki Ito, Joonas Jälkö, Yuan He, Antti Honkela

TMLR 2025 NeurIPS 2023 Competition: Privacy Preserving Federated Learning Document VQA Marlon Tobaben, Mohamed Ali Souibgui, Rubèn Tito, Khanh Nguyen, Raouf Kerkouche, Kangsoo Jung, Joonas Jälkö, Lei Kang, Andrey Barsky, Vincent Poulain d'Andecy, Aurélie Joseph, Aashiq Muhamed, Kevin Kuo, Virginia Smith, Yusuke Yamasaki, Takumi Fukami, Kenta Niwa, Iifan Tyou, Hiro Ishii, Rio Yokota, Ragul N, Rintu Kutum, Josep Llados, Ernest Valveny, Antti Honkela, Mario Fritz, Dimosthenis Karatzas

AISTATS 2025 Noise-Aware Differentially Private Variational Inference Talal Alrawajfeh, Joonas Jälkö, Antti Honkela

JMLR 2025 On Consistent Bayesian Inference from Synthetic Data Ossi Räisä, Joonas Jälkö, Antti Honkela

ICLRW 2024 Subsampling Is Not Magic: Why Large Batch Sizes Work for Differentially Private Stochastic Optimisation Ossi Räisä, Joonas Jälkö, Antti Honkela

ICML 2024 Subsampling Is Not Magic: Why Large Batch Sizes Work for Differentially Private Stochastic Optimisation Ossi Räisä, Joonas Jälkö, Antti Honkela

ICLRW 2024 Understanding Practical Membership Privacy of Deep Learning Marlon Tobaben, Gauri Pradhan, Yuan He, Joonas Jälkö, Antti Honkela

TMLR 2023 DPVIm: Differentially Private Variational Inference Improved Joonas Jälkö, Lukas Prediger, Antti Honkela, Samuel Kaski

AISTATS 2023 Noise-Aware Statistical Inference with Differentially Private Synthetic Data Ossi Räisä, Joonas Jälkö, Samuel Kaski, Antti Honkela

NeurIPSW 2023 On Consistent Bayesian Inference from Synthetic Data Ossi Räisä, Joonas Jälkö, Antti Honkela

NeurIPSW 2022 Noise-Aware Statistical Inference with Differentially Private Synthetic Data Ossi Räisä, Joonas Jälkö, Samuel Kaski, Antti Honkela

AISTATS 2021 Tight Differential Privacy for Discrete-Valued Mechanisms and for the Subsampled Gaussian Mechanism Using FFT Antti Koskela, Joonas Jälkö, Lukas Prediger, Antti Honkela

ICML 2021 Differentially Private Bayesian Inference for Generalized Linear Models Tejas Kulkarni, Joonas Jälkö, Antti Koskela, Samuel Kaski, Antti Honkela

AISTATS 2020 Computing Tight Differential Privacy Guarantees Using FFT Antti Koskela, Joonas Jälkö, Antti Honkela

NeurIPS 2019 Differentially Private Markov Chain Monte Carlo Mikko Heikkilä, Joonas Jälkö, Onur Dikmen, Antti Honkela

UAI 2017 Differentially Private Variational Inference for Non-Conjugate Models Joonas Jälkö, Antti Honkela, Onur Dikmen