Antti Koskela
Antti Koskela
Nokia Bell Labs
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Computing Tight Differential Privacy Guarantees Using FFT
A Koskela, J Jälkö, A Honkela
International Conference on Artificial Intelligence and Statistics, 2560-2569, 2020
Ethylene glycol revisited: Molecular dynamics simulations and visualization of the liquid and its hydrogen-bond network
A Kaiser, O Ismailova, A Koskela, SE Huber, M Ritter, B Cosenza, ...
Journal of Molecular Liquids 189, 20-29, 2014
Tight differential privacy for discrete-valued mechanisms and for the subsampled gaussian mechanism using FFT
A Koskela, J Jälkö, L Prediger, A Honkela
International Conference on Artificial Intelligence and Statistics, 3358-3366, 2021
Learning rate adaptation for differentially private learning
A Koskela, A Honkela
International Conference on Artificial Intelligence and Statistics, 2465-2475, 2020
Differentially private cross-silo federated learning
MA Heikkilä, A Koskela, K Shimizu, S Kaski, A Honkela
arXiv preprint arXiv:2007.05553, 2020
Differentially private Bayesian inference for generalized linear models
T Kulkarni, J Jälkö, A Koskela, S Kaski, A Honkela
International Conference on Machine Learning, 5838-5849, 2021
Exponential Taylor methods: Analysis and implementation
A Koskela, A Ostermann
Computers & Mathematics with Applications 65 (3), 487-499, 2013
Splitting methods for time integration of trajectories in combined electric and magnetic fields
C Knapp, A Kendl, A Koskela, A Ostermann
Physical Review E 92 (6), 063310, 2015
Analysis of Krylov Subspace Approximation to Large Scale Differential Riccati Equations
A Koskela, H Mena
Electronic Transactions on Numerical Analysis 52, 431--454, 2020
Computing low-rank approximations of the Fréchet derivative of a matrix function using Krylov subspace methods
P Kandolf, A Koskela, SD Relton, M Schweitzer
Numerical Linear Algebra with Applications, e2401, 2021
Numerical Accounting in the Shuffle Model of Differential Privacy
A Koskela, M Heikkilä, A Honkela
Transactions on Machine Learning Research, 2023
Approximating the matrix exponential of an advection-diffusion operator using the incomplete orthogonalization method
A Koskela
Numerical Mathematics and Advanced Applications-ENUMATH 2013: Proceedings of …, 2014
Computing differential privacy guarantees for heterogeneous compositions using FFT
A Koskela, A Honkela
arXiv preprint arXiv:2102.12412, 2021
Individual Privacy Accounting with Gaussian Differential Privacy
A Koskela, M Tobaben, A Honkela
International Conference on Learning Representations, 2023
Disguised and new quasi-Newton methods for nonlinear eigenvalue problems
E Jarlebring, A Koskela, G Mele
Numerical Algorithms 79, 311-335, 2018
Differentially private hamiltonian monte carlo
O Räisä, A Koskela, A Honkela
arXiv preprint arXiv:2106.09376, 2021
Krylov integrators for Hamiltonian systems
T Eirola, A Koskela
BIT Numerical Mathematics 59, 57-76, 2019
Practical differentially private hyperparameter tuning with subsampling
A Koskela, T Kulkarni
Thirty-seventh Conference on Neural Information Processing Systems, 2023
The infinite Arnoldi exponential integrator for linear inhomogeneous ODEs
A Koskela, E Jarlebring
arXiv preprint arXiv:1502.01613, 2015
A Moment-Matching Arnoldi Iteration for Linear Combinations of Functions
A Koskela, A Ostermann
SIAM Journal on Matrix Analysis and Applications 35 (4), 1344-1363, 2014
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