Antti Honkela - RankMe

102 papers A* 5A 8B 5C 1Journal 74Unranked 9

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	(ϵ, δ) Considered Harmful: Best Practices for Reporting Differential Privacy Guarantees. CoRR Juan Felipe Gómez, Bogdan Kulynych, Georgios Kaissis, Jamie Hayes, Borja Balle, Antti Honkela
2025	A	`conf`	A Bias-Variance Decomposition for Ensembles over Multiple Synthetic Datasets. AISTATS Ossi Räisä, Antti Honkela
2025	J	`jnl`	Accuracy-First Rényi Differential Privacy and Post-Processing Immunity. CoRR Ossi Räisä, Antti Koskela, Antti Honkela
2025	J	`jnl`	An Interactive Framework for Finding the Optimal Trade-off in Differential Privacy. CoRR Yaohong Yang, Aki Rehn, Sammie Katt, Antti Honkela, Samuel Kaski
2025	J	`jnl`	Beyond Membership: Limitations of Add/Remove Adjacency in Differential Privacy. CoRR Gauri Pradhan, Joonas Jälkö, Santiago Zanella-Béguelin, Antti Honkela
2025	J	`jnl`	Empirical Comparison of Membership Inference Attacks in Deep Transfer Learning. CoRR Yuxuan Bai, Gauri Pradhan, Marlon Tobaben, Antti Honkela
2025	J	`jnl`	Empirical Comparison of Membership Inference Attacks in Deep Transfer Learning. Trans. Mach. Learn. Res. Yuxuan Bai, Gauri Pradhan, Marlon Tobaben, 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`	Mitigating Disparate Impact of Differentially Private Learning through Bounded Adaptive Clipping. CoRR Linzh Zhao, Aki Rehn, Mikko A. Heikkilä, Razane Tajeddine, 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
2025	J	`jnl`	On Optimal Hyperparameters for Differentially Private Deep Transfer Learning. CoRR Aki Rehn, Linzh Zhao, Mikko A. Heikkilä, Antti Honkela
2024	J	`jnl`	A Bias-Variance Decomposition for Ensembles over Multiple Synthetic Datasets. CoRR Ossi Räisä, 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`	Differentially Private Continual Learning using Pre-Trained Models. CoRR Marlon Tobaben, Marcus Klasson, Rui Li, Arno Solin, Antti Honkela
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	A*	`conf`	Noise-Aware Differentially Private Regression via Meta-Learning. NeurIPS Ossi Räisä, Stratis Markou, Matthew Ashman, Wessel P. Bruinsma, Marlon Tobaben, Antti Honkela, Richard E. Turner
2024	J	`jnl`	Noise-Aware Differentially Private Regression via Meta-Learning. CoRR Ossi Räisä, Stratis Markou, Matthew Ashman, Wessel P. Bruinsma, Marlon Tobaben, Antti Honkela, Richard E. Turner
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`	Towards Efficient and Scalable Training of Differentially Private Deep Learning. CoRR Sebastian Rodriguez Beltran, Marlon Tobaben, Niki Andreas Lopi, 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	J	`jnl`	Differentially private partitioned variational inference. Trans. Mach. Learn. Res. Mikko A. Heikkilä, Matthew Ashman, Siddharth Swaroop, Richard E. Turner, Antti Honkela
2023	A*	`conf`	Individual Privacy Accounting with Gaussian Differential Privacy. ICLR Antti Koskela, Marlon Tobaben, Antti Honkela
2023	A	`conf`	Noise-Aware Statistical Inference with Differentially Private Synthetic Data. AISTATS Ossi Räisä, Joonas Jälkö, Samuel Kaski, 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	J	`jnl`	On the Efficacy of Differentially Private Few-shot Image Classification. CoRR Marlon Tobaben, Aliaksandra Shysheya, John Bronskill, Andrew Paverd, Shruti Tople, Santiago Zanella-Béguelin, Richard E. Turner, Antti Honkela
2023	J	`jnl`	On the Efficacy of Differentially Private Few-shot Image Classification. Trans. Mach. Learn. Res. Marlon Tobaben, Aliaksandra Shysheya, John Bronskill, Andrew Paverd, Shruti Tople, Santiago Zanella-Béguelin, Richard E. Turner, Antti Honkela
2023	J	`jnl`	Privacy-Aware Document Visual Question Answering. CoRR Rubèn Tito, Khanh Nguyen, Marlon Tobaben, Raouf Kerkouche, Mohamed Ali Souibgui, Kangsoo Jung, Lei Kang, Ernest Valveny, Antti Honkela, Mario Fritz, Dimosthenis Karatzas
2022	J	`jnl`	DPVIm: Differentially Private Variational Inference Improved. CoRR Joonas Jälkö, Lukas Prediger, Antti Honkela, Samuel Kaski
2022	J	`jnl`	Differentially private partitioned variational inference. CoRR Mikko A. Heikkilä, Matthew Ashman, Siddharth Swaroop, Richard E. Turner, Antti Honkela
2022	J	`jnl`	Individual Privacy Accounting with Gaussian Differential Privacy. CoRR Antti Koskela, Marlon Tobaben, Antti Honkela
2022	J	`jnl`	Noise-Aware Statistical Inference with Differentially Private Synthetic Data. CoRR Ossi Räisä, Joonas Jälkö, Samuel Kaski, Antti Honkela
2022	J	`jnl`	d3p - A Python Package for Differentially-Private Probabilistic Programming. Proc. Priv. Enhancing Technol. Lukas Prediger, Niki Andreas Lopi, Samuel Kaski, Antti Honkela
2021	J	`jnl`	Computing Differential Privacy Guarantees for Heterogeneous Compositions Using FFT. CoRR Antti Koskela, 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`	Differentially Private Hamiltonian Monte Carlo. CoRR Ossi Räisä, Antti Koskela, Antti Honkela
2021	J	`jnl`	Gaussian Processes with Differential Privacy. CoRR 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	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
2021	J	`jnl`	d3p - A Python Package for Differentially-Private Probabilistic Programming. CoRR Lukas Prediger, Niki Andreas Lopi, Samuel Kaski, 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`	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`	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	J	`jnl`	Differentially Private Federated Variational Inference. CoRR Mrinank Sharma, Michael J. Hutchinson, Siddharth Swaroop, Antti Honkela, Richard E. Turner
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
2019	J	`jnl`	Representation Transfer for Differentially Private Drug Sensitivity Prediction. CoRR Teppo Mikael Niinimäki, Mikko A. Heikkilä, Antti Honkela, Samuel Kaski
2019	J	`jnl`	Representation transfer for differentially private drug sensitivity prediction. Bioinform. Teppo Mikael Niinimäki, Mikko A. Heikkilä, Antti Honkela, Samuel Kaski
2018	J	`jnl`	Learning rate adaptation for differentially private stochastic gradient descent. CoRR Antti Koskela, Antti Honkela
2017	J	`jnl`	Differentially Private Bayesian Learning on Distributed Data. CoRR Mikko A. Heikkilä, Yusuke Okimoto, Samuel Kaski, Kana Shimizu, Antti Honkela
2017	A	`conf`	Differentially Private Variational Inference for Non-conjugate Models. UAI Joonas Jälkö, Antti Honkela, Onur Dikmen
2017	—	`conf`	Differentially private Bayesian learning on distributed data. NIPS Mikko A. Heikkilä, Eemil Lagerspetz, Samuel Kaski, Kana Shimizu, Sasu Tarkoma, Antti Honkela
2016	J	`jnl`	Analysis of differential splicing suggests different modes of short-term splicing regulation. Bioinform. Hande Topa, Antti Honkela
2016	J	`jnl`	Differentially Private Variational Inference for Non-conjugate Models. CoRR Joonas Jälkö, Onur Dikmen, Antti Honkela
2016	J	`jnl`	Efficient differentially private learning improves drug sensitivity prediction. CoRR Antti Honkela, Mrinal Das, Onur Dikmen, Samuel Kaski
2016	J	`jnl`	On the inconsistency of ℓ CoRR Otte Heinävaara, Janne Leppä-aho, Jukka Corander, Antti Honkela
2016	J	`jnl`	On the inconsistency of ℓ 1-penalised sparse precision matrix estimation. BMC Bioinform. Otte Heinävaara, Janne Leppä-aho, Jukka Corander, Antti Honkela
2015	J	`jnl`	Fast and accurate approximate inference of transcript expression from RNA-seq data. Bioinform. James Hensman, Panagiotis Papastamoulis, Peter Glaus, Antti Honkela, Magnus Rattray
2015	B	`conf`	Gaussian process modelling of multiple short time series. ESANN Hande Topa, Antti Honkela
2015	J	`jnl`	Gaussian process test for high-throughput sequencing time series: application to experimental evolution. Bioinform. Hande Topa, Ágnes Jónás, Robert Kofler, Carolin Kosiol, Antti Honkela
2014	J	`jnl`	Exploration and retrieval of whole-metagenome sequencing samples. Bioinform. Sohan Seth, Niko Välimäki, Samuel Kaski, Antti Honkela
2014	J	`jnl`	Inference of RNA Polymerase II Transcription Dynamics from Chromatin Immunoprecipitation Time Course Data. PLoS Comput. Biol. Ciira Wa Maina, Antti Honkela, Filomena Matarese, Korbinian Grote, Hendrik G. Stunnenberg, George Reid, Neil D. Lawrence, Magnus Rattray
2013	J	`jnl`	Exploration and retrieval of whole-metagenome sequencing samples. CoRR Sohan Seth, Niko Välimäki, Samuel Kaski, Antti Honkela
2012	J	`jnl`	Bayes Blocks: An Implementation of the Variational Bayesian Building Blocks Framework CoRR Markus Harva, Tapani Raiko, Antti Honkela, Harri Valpola, Juha Karhunen
2012	J	`jnl`	Identifying differentially expressed transcripts from RNA-seq data with biological variation. Bioinform. Peter Glaus, Antti Honkela, Magnus Rattray
2012	J	`jnl`	Identifying targets of multiple co-regulating transcription factors from expression time-series by Bayesian model comparison. BMC Syst. Biol. Michalis K. Titsias, Antti Honkela, Neil D. Lawrence, Magnus Rattray
2011	—	`conf`	A Generative Approach for Image-Based Modeling of Tumor Growth. IPMI Bjoern H. Menze, Koen Van Leemput, Antti Honkela, Ender Konukoglu, Marc-André Weber, Nicholas Ayache, Polina Golland
2011	J	`jnl`	Missing-Feature Reconstruction With a Bounded Nonlinear State-Space Model. IEEE Signal Process. Lett. Ulpu Remes, Kalle J. Palomäki, Tapani Raiko, Antti Honkela, Mikko Kurimo
2011	J	`jnl`	tigre: Transcription factor inference through gaussian process reconstruction of expression for bioconductor. Bioinform. Antti Honkela, Pei Gao, Jonatan Ropponen, Magnus Rattray, Neil D. Lawrence
2010	J	`jnl`	Approximate Riemannian Conjugate Gradient Learning for Fixed-Form Variational Bayes. J. Mach. Learn. Res. Antti Honkela, Tapani Raiko, Mikael Kuusela, Matti Tornio, Juha Karhunen
2010	J	`jnl`	Model-based method for transcription factor target identification with limited data. Proc. Natl. Acad. Sci. USA Antti Honkela, Charles Girardot, Eleanor Hilary Gustafson, Ya-Hsin Liu, Eileen E. M. Furlong, Neil D. Lawrence, Magnus Rattray
2009	B	`conf`	A gradient-based algorithm competitive with variational Bayesian EM for mixture of Gaussians. IJCNN Mikael Kuusela, Tapani Raiko, Antti Honkela, Juha Karhunen
2008	J	`jnl`	Agglomerative independent variable group analysis. Neurocomputing Antti Honkela, Jeremias Seppä, Esa Alhoniemi
2008	C	`conf`	Gaussian process modelling of latent chemical species: applications to inferring transcription factor activities. ECCB Pei Gao, Antti Honkela, Magnus Rattray, Neil D. Lawrence
2007	B	`conf`	Agglomerative Independent Variable Group Analysis. ESANN Antti Honkela, Jeremias Seppä, Esa Alhoniemi
2007	J	`jnl`	Blind separation of nonlinear mixtures by variational Bayesian learning. Digit. Signal Process. Antti Honkela, Harri Valpola, Alexander Ilin, Juha Karhunen
2007	J	`jnl`	Compact Modeling of Data Using Independent Variable Group Analysis. IEEE Trans. Neural Networks Esa Alhoniemi, Antti Honkela, Krista Lagus, Santeri Jeremias Seppä, Paul Wagner, Harri Valpola
2007	—	`conf`	Natural Conjugate Gradient in Variational Inference. ICONIP (2) Antti Honkela, Matti Tornio, Tapani Raiko, Juha Karhunen
2006	—	`conf`	State Inference in Variational Bayesian Nonlinear State-Space Models. ICA Tapani Raiko, Matti Tornio, Antti Honkela, Juha Karhunen
2005	A	`conf`	Bayes Blocks: An Implementation of the Variational Bayesian Building Blocks Framework. UAI Markus Harva, Tapani Raiko, Antti Honkela, Harri Valpola, Juha Karhunen
2005	B	`conf`	Empirical evidence of the linear nature of magnetoencephalograms. ESANN Antti Honkela, Tomas Östman, Ricardo Vigário
2004	B	`conf`	Approximating nonlinear transformations of probability distributions for nonlinear independent component analysis. IJCNN Antti Honkela
2004	—	`conf`	Post-nonlinear Independent Component Analysis by Variational Bayesian Learning. ICA Alexander Ilin, Antti Honkela
2004	—	`conf`	Unsupervised Variational Bayesian Learning of Nonlinear Models. NIPS Antti Honkela, Harri Valpola
2004	—	`conf`	Using Kernel PCA for Initialisation of Variational Bayesian Nonlinear Blind Source Separation Method. ICA Antti Honkela, Stefan Harmeling, Leo Lundqvist, Harri Valpola
2004	J	`jnl`	Variational learning and bits-back coding: an information-theoretic view to Bayesian learning. IEEE Trans. Neural Networks Antti Honkela, Harri Valpola
2003	J	`jnl`	Accelerating Cyclic Update Algorithms for Parameter Estimation by Pattern Searches. Neural Process. Lett. Antti Honkela, Harri Valpola, Juha Karhunen
2003	J	`jnl`	Nonlinear Blind Source Separation by Variational Bayesian Learning. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. Harri Valpola, Erkki Oja, Alexander Ilin, Antti Honkela, Juha Karhunen