Antti Koskela - RankMe

41 papers A* 5A 3B 1Journal 30Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	On the Price of Differential Privacy for Spectral Clustering Over Stochastic Block Models. IEEE Trans. Netw. Sci. Eng. Antti Koskela, Mohamed Seif, Andrea J. Goldsmith
2025	J	`jnl`	Accuracy-First Rényi Differential Privacy and Post-Processing Immunity. CoRR Ossi Räisä, Antti Koskela, Antti Honkela
2025	—	`conf`	Auditing Differential Privacy Guarantees Using Density Estimation. SaTML Antti Koskela, Jafar Mohammadi
2025	J	`jnl`	Communication Efficient Differentially Private Federated Learning Using Second Order Information. Proc. Priv. Enhancing Technol. Mounssif Krouka, Antti Koskela, Tejas D. Kulkarni
2025	J	`jnl`	Differential Privacy Analysis of Decentralized Gossip Averaging under Varying Threat Models. CoRR Antti Koskela, Tejas D. Kulkarni
2025	J	`jnl`	Differentially Private In-Context Learning with Nearest Neighbor Search. CoRR Antti Koskela, Tejas D. Kulkarni, Laith Y. Zumot
2025	J	`jnl`	On the Price of Differential Privacy for Spectral Clustering over Stochastic Block Models. CoRR Antti Koskela, Mohamed Seif, Andrea J. Goldsmith
2025	B	`conf`	Private Spectral Clustering Over Binary Stochastic Block Models. ISIT Mohamed Seif, Antti Koskela, Andrea J. Goldsmith
2025	J	`jnl`	Spectral Graph Clustering under Differential Privacy: Balancing Privacy, Accuracy, and Efficiency. CoRR Mohamed Seif, Antti Koskela, H. Vincent Poor, Andrea J. Goldsmith
2024	J	`jnl`	Black Box Differential Privacy Auditing Using Total Variation Distance. CoRR Antti Koskela, Jafar Mohammadi
2024	J	`jnl`	Differentially Private Convex Approximation of Two-Layer ReLU Networks. CoRR Antti Koskela
2024	J	`jnl`	Improving the Privacy and Practicality of Objective Perturbation for Differentially Private Linear Learners. CoRR Rachel Redberg, Antti Koskela, Yu-Xiang Wang
2024	A*	`conf`	Privacy Profiles for Private Selection. ICML Antti Koskela, Rachel Redberg, Yu-Xiang Wang
2024	J	`jnl`	Privacy Profiles for Private Selection. CoRR Antti Koskela, Rachel Redberg, Yu-Xiang Wang
2024	J	`jnl`	Protecting Confidentiality, Privacy and Integrity in Collaborative Learning. CoRR Dong Chen, Alice Dethise, Istemi Ekin Akkus, Ivica Rimac, Klaus Satzke, Antti Koskela, Marco Canini, Wei Wang, Ruichuan Chen
2023	A*	`conf`	Improving the Privacy and Practicality of Objective Perturbation for Differentially Private Linear Learners. NeurIPS Rachel Redberg, Antti Koskela, Yu-Xiang Wang
2023	A*	`conf`	Individual Privacy Accounting with Gaussian Differential Privacy. ICLR Antti Koskela, Marlon Tobaben, Antti Honkela
2023	J	`jnl`	Numerical Accounting in the Shuffle Model of Differential Privacy. Trans. Mach. Learn. Res. Antti Koskela, Mikko A. Heikkilä, Antti Honkela
2023	A*	`conf`	Practical Differentially Private Hyperparameter Tuning with Subsampling. NeurIPS Antti Koskela, Tejas D. Kulkarni
2023	J	`jnl`	Practical Differentially Private Hyperparameter Tuning with Subsampling. CoRR Antti Koskela, Tejas Kulkarni
2022	J	`jnl`	Individual Privacy Accounting with Gaussian Differential Privacy. CoRR Antti Koskela, Marlon Tobaben, Antti Honkela
2021	J	`jnl`	Computing Differential Privacy Guarantees for Heterogeneous Compositions Using FFT. CoRR Antti Koskela, Antti Honkela
2021	J	`jnl`	Computing low-rank approximations of the Fréchet derivative of a matrix function using Krylov subspace methods. Numer. Linear Algebra Appl. Peter Kandolf, Antti Koskela, Samuel D. Relton, Marcel Schweitzer
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`	Differentially Private Hamiltonian Monte Carlo. CoRR Ossi Räisä, Antti Koskela, Antti Honkela
2021	J	`jnl`	Tight Accounting in the Shuffle Model of Differential Privacy. CoRR Antti Koskela, Mikko A. Heikkilä, Antti Honkela
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`	Computing low-rank approximations of the Fréchet derivative of a matrix function using Krylov subspace methods. CoRR Peter Kandolf, Antti Koskela, Samuel D. Relton, Marcel Schweitzer
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`	Differentially private cross-silo federated learning. CoRR Mikko A. Heikkilä, Antti Koskela, Kana Shimizu, Samuel Kaski, Antti Honkela
2020	A	`conf`	Learning Rate Adaptation for Differentially Private Learning. AISTATS Antti Koskela, Antti Honkela
2020	J	`jnl`	Sampling of Stochastic Differential Equations using the Karhunen-Loève Expansion and Matrix Functions. CoRR Antti Koskela, Samuel D. Relton
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
2018	J	`jnl`	Disguised and new quasi-Newton methods for nonlinear eigenvalue problems. Numer. Algorithms Elias Jarlebring, Antti Koskela, Giampaolo Mele
2018	J	`jnl`	Learning rate adaptation for differentially private stochastic gradient descent. CoRR Antti Koskela, Antti Honkela
2016	J	`jnl`	Krylov Approximation of Linear ODEs with Polynomial Parameterization. SIAM J. Matrix Anal. Appl. Antti Koskela, Elias Jarlebring, Michiel E. Hochstenbach
2014	J	`jnl`	A Moment-Matching Arnoldi Iteration for Linear Combinations of φ Functions. SIAM J. Matrix Anal. Appl. Antti Koskela, Alexander Ostermann
2013	—	`conf`	Approximating the Matrix Exponential of an Advection-Diffusion Operator Using the Incomplete Orthogonalization Method. ENUMATH Antti Koskela
2013	J	`jnl`	Exponential Taylor methods: Analysis and implementation. Comput. Math. Appl. Antti Koskela, Alexander Ostermann