Joonas Jälkö

32 papers A* 3A 5Journal 22Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Beyond Membership: Limitations of Add/Remove Adjacency in Differential Privacy. CoRR Gauri Pradhan, Joonas Jälkö, Santiago Zanella-Béguelin, Antti Honkela
2025	—	`conf`	Hyperparameters in Score-Based Membership Inference Attacks. SaTML Gauri Pradhan, Joonas Jälkö, Marlon Tobaben, Antti Honkela
2025	J	`jnl`	Hyperparameters in Score-Based Membership Inference Attacks. CoRR Gauri Pradhan, Joonas Jälkö, Marlon Tobaben, Antti Honkela
2025	J	`jnl`	NeurIPS 2023 Competition: Privacy Preserving Federated Learning Document VQA. Trans. Mach. Learn. Res. 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 Lladós, Ernest Valveny, Antti Honkela, Mario Fritz, Dimosthenis Karatzas
2025	A	`conf`	Noise-Aware Differentially Private Variational Inference. AISTATS Talal Alrawajfeh, Joonas Jälkö, Antti Honkela
2025	J	`jnl`	On Consistent Bayesian Inference from Synthetic Data. J. Mach. Learn. Res. Ossi Räisä, Joonas Jälkö, Antti Honkela
2024	J	`jnl`	Collaborative learning from distributed data with differentially private synthetic data. BMC Medical Informatics Decis. Mak. Lukas Prediger, Joonas Jälkö, Antti Honkela, Samuel Kaski
2024	J	`jnl`	NeurIPS 2023 Competition: Privacy Preserving Federated Learning Document VQA. CoRR 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 Lladós, Ernest Valveny, Antti Honkela, Mario Fritz, Dimosthenis Karatzas
2024	J	`jnl`	Noise-Aware Differentially Private Variational Inference. CoRR Talal Alrawajfeh, Joonas Jälkö, Antti Honkela
2024	—	`conf`	Privacy-Aware Document Visual Question Answering. ICDAR (6) Rubèn Tito, Khanh Nguyen, Marlon Tobaben, Raouf Kerkouche, Mohamed Ali Souibgui, Kangsoo Jung, Joonas Jälkö, Vincent Poulain D'Andecy, Aurélie Joseph, Lei Kang, Ernest Valveny, Antti Honkela, Mario Fritz, Dimosthenis Karatzas
2024	A*	`conf`	Subsampling is not Magic: Why Large Batch Sizes Work for Differentially Private Stochastic Optimisation. ICML Ossi Räisä, Joonas Jälkö, Antti Honkela
2024	J	`jnl`	Subsampling is not Magic: Why Large Batch Sizes Work for Differentially Private Stochastic Optimisation. CoRR Ossi Räisä, Joonas Jälkö, Antti Honkela
2024	J	`jnl`	Understanding Practical Membership Privacy of Deep Learning. CoRR Marlon Tobaben, Gauri Pradhan, Yuan He, Joonas Jälkö, Antti Honkela
2023	J	`jnl`	Collaborative Learning From Distributed Data With Differentially Private Synthetic Twin Data. CoRR Lukas Prediger, Joonas Jälkö, Antti Honkela, Samuel Kaski
2023	J	`jnl`	DPVIm: Differentially Private Variational Inference Improved. Trans. Mach. Learn. Res. Joonas Jälkö, Lukas Prediger, Antti Honkela, Samuel Kaski
2023	A	`conf`	Noise-Aware Statistical Inference with Differentially Private Synthetic Data. AISTATS Ossi Räisä, Joonas Jälkö, Samuel Kaski, Antti Honkela
2022	J	`jnl`	DPVIm: Differentially Private Variational Inference Improved. CoRR Joonas Jälkö, Lukas Prediger, Antti Honkela, Samuel Kaski
2022	J	`jnl`	Noise-Aware Statistical Inference with Differentially Private Synthetic Data. CoRR Ossi Räisä, Joonas Jälkö, Samuel Kaski, Antti Honkela
2021	A*	`conf`	Differentially Private Bayesian Inference for Generalized Linear Models. ICML Tejas Kulkarni, Joonas Jälkö, Antti Koskela, Samuel Kaski, Antti Honkela
2021	J	`jnl`	Locally Differentially Private Bayesian Inference. CoRR Tejas Kulkarni, Joonas Jälkö, Samuel Kaski, Antti Honkela
2021	J	`jnl`	Privacy-preserving data sharing via probabilistic modeling. Patterns Joonas Jälkö, Eemil Lagerspetz, Jari Haukka, Sasu Tarkoma, Antti Honkela, Samuel Kaski
2021	A	`conf`	Tight Differential Privacy for Discrete-Valued Mechanisms and for the Subsampled Gaussian Mechanism Using FFT. AISTATS Antti Koskela, Joonas Jälkö, Lukas Prediger, Antti Honkela
2020	A	`conf`	Computing Tight Differential Privacy Guarantees Using FFT. AISTATS Antti Koskela, Joonas Jälkö, Antti Honkela
2020	J	`jnl`	Differentially Private Bayesian Inference for Generalized Linear Models. CoRR Tejas Kulkarni, Joonas Jälkö, Antti Koskela, Samuel Kaski, Antti Honkela
2020	J	`jnl`	Privacy-preserving Data Sharing on Vertically Partitioned Data. CoRR Razane Tajeddine, Joonas Jälkö, Samuel Kaski, Antti Honkela
2020	J	`jnl`	Tight Approximate Differential Privacy for Discrete-Valued Mechanisms Using FFT. CoRR Antti Koskela, Joonas Jälkö, Lukas Prediger, Antti Honkela
2019	J	`jnl`	Computing Exact Guarantees for Differential Privacy. CoRR Antti Koskela, Joonas Jälkö, Antti Honkela
2019	A*	`conf`	Differentially Private Markov Chain Monte Carlo. NeurIPS Mikko A. Heikkilä, Joonas Jälkö, Onur Dikmen, Antti Honkela
2019	J	`jnl`	Differentially Private Markov Chain Monte Carlo. CoRR Mikko A. Heikkilä, Joonas Jälkö, Onur Dikmen, Antti Honkela
2019	J	`jnl`	Privacy-preserving data sharing via probabilistic modelling. CoRR Joonas Jälkö, Eemil Lagerspetz, Jari Haukka, Sasu Tarkoma, Samuel Kaski, Antti Honkela
2017	A	`conf`	Differentially Private Variational Inference for Non-conjugate Models. UAI Joonas Jälkö, Antti Honkela, Onur Dikmen
2016	J	`jnl`	Differentially Private Variational Inference for Non-conjugate Models. CoRR Joonas Jälkö, Onur Dikmen, Antti Honkela