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Tight Accounting in the Shuffle Model of Differential Privacy


Jun 01, 2021
Antti Koskela, Mikko A. Heikkilä, Antti Honkela

* 24 pages, 10 figures 

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Gaussian Processes with Differential Privacy


Jun 01, 2021
Antti Honkela


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d3p -- A Python Package for Differentially-Private Probabilistic Programming


Mar 22, 2021
Lukas Prediger, Niki Loppi, Samuel Kaski, Antti Honkela


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Computing Differential Privacy Guarantees for Heterogeneous Compositions Using FFT


Feb 24, 2021
Antti Koskela, Antti Honkela

* 32 pages, 2 figures. arXiv admin note: text overlap with arXiv:2006.07134 

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Differentially Private Bayesian Inference for Generalized Linear Models


Nov 09, 2020
Tejas Kulkarni, Joonas Jälkö, Antti Koskela, Samuel Kaski, Antti Honkela


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Privacy-preserving Data Sharing on Vertically Partitioned Data


Oct 19, 2020
Razane Tajeddine, Joonas Jälkö, Samuel Kaski, Antti Honkela


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Differentially private cross-silo federated learning


Jul 10, 2020
Mikko A. Heikkilä, Antti Koskela, Kana Shimizu, Samuel Kaski, Antti Honkela

* 14 pages, 5 figures 

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Tight Approximate Differential Privacy for Discrete-Valued Mechanisms Using FFT


Jun 12, 2020
Antti Koskela, Joonas Jälkö, Lukas Prediger, Antti Honkela

* 32 pages, 5 figures 

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Privacy-preserving data sharing via probabilistic modelling


Jan 29, 2020
Joonas Jälkö, Eemil Lagerspetz, Jari Haukka, Sasu Tarkoma, Samuel Kaski, Antti Honkela


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Differentially Private Federated Variational Inference


Nov 24, 2019
Mrinank Sharma, Michael Hutchinson, Siddharth Swaroop, Antti Honkela, Richard E. Turner

* Privacy in Machine Learning Workshop (PriML 2019) at the 33rd Conference in Neural Information and Processing Systems (NeurIPS) 

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Computing Exact Guarantees for Differential Privacy


Jun 07, 2019
Antti Koskela, Joonas Jälkö, Antti Honkela

* 24 pages, 5 figures 

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Differentially Private Markov Chain Monte Carlo


Jan 29, 2019
Mikko A. Heikkilä, Joonas Jälkö, Onur Dikmen, Antti Honkela

* 24 pages, 12 figures 

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Representation Transfer for Differentially Private Drug Sensitivity Prediction


Jan 29, 2019
Teppo Niinimäki, Mikko Heikkilä, Antti Honkela, Samuel Kaski

* 12 pages, 5 figures 

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Learning rate adaptation for differentially private stochastic gradient descent


Sep 11, 2018
Antti Koskela, Antti Honkela

* 17 pages, 7 figures 

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Efficient differentially private learning improves drug sensitivity prediction


Jul 05, 2017
Antti Honkela, Mrinal Das, Arttu Nieminen, Onur Dikmen, Samuel Kaski

* Biology Direct (2018) 13:1 
* 14 pages + 13 pages supplementary information, 3 + 3 figures 

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Differentially Private Bayesian Learning on Distributed Data


May 29, 2017
Mikko Heikkilä, Eemil Lagerspetz, Samuel Kaski, Kana Shimizu, Sasu Tarkoma, Antti Honkela

* 13 pages, 7 figures. Modified text, changed algorithm used, included tests on additional dataset, fixed several errors, added proof of asymptotic efficiency to supplement 

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Differentially Private Variational Inference for Non-conjugate Models


Apr 10, 2017
Joonas Jälkö, Onur Dikmen, Antti Honkela

* 10 pages, 5 figures 

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On the inconsistency of $\ell_1$-penalised sparse precision matrix estimation


Mar 08, 2016
Otte Heinävaara, Janne Leppä-aho, Jukka Corander, Antti Honkela

* 9 pages, 10 figures 

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Gaussian process modelling of multiple short time series


Oct 09, 2012
Hande Topa, Antti Honkela

* 11 pages, 6 figures 

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Bayes Blocks: An Implementation of the Variational Bayesian Building Blocks Framework


Jul 04, 2012
Markus Harva, Tapani Raiko, Antti Honkela, Harri Valpola, Juha Karhunen

* Appears in Proceedings of the Twenty-First Conference on Uncertainty in Artificial Intelligence (UAI2005) 

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