Antti Honkela
14 papers · 2010–2025 · 5 venues · across top CS/AI venues
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Achievements
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🏃 Academic Marathon · Full 🐣 Hot Topic Early Bird 🌉 Interdisciplinary Bridge · Silver 🌍 Conference Polyglot · Silver 🗺️ Taxonomy Completionist (24)
🏆
Keyword Champion
(3)
📈
Trend Setter
💎
Century Club · Bronze
🗃️
Keyword Collector
(54)
Top co-authors
Research topics
Machine Learning
(13)
Optimization & Theory
(11)
Application Areas
(10)
Artificial Intelligence
(6)
Security & Privacy
(5)
Differential Privacy
(5)
Bayesian & Probabilistic · Machine Learning
(3)
Mathematics & Optimization
(2)
Bayesian & Probabilistic · Artificial Intelligence
(2)
Core AI
(2)
Core Methods
(2)
Learning Paradigms
(2)
Learning Types
(2)
Data Science & Analytics
(1)
Deep Learning
(1)
Keywords
differential privacy
(12)
bayesian inference
(5)
gaussian mechanism
(3)
synthetic data
(3)
privacy accounting
(3)
fast fourier transform
(2)
privacy loss distribution
(2)
posterior inference
(2)
uncertainty estimation
(2)
markov chain monte carlo
(1)
synthetic data generation
(1)
privacy-preserving learning
(1)
bayesian learning
(1)
bayesian modeling
(1)
stochastic gradient descent
(1)
posterior sampling
(1)
learning rate adaptation
(1)
distributed learning
(1)
variational inference
(1)
mean squared error
(1)
Papers
A Bias-Variance Decomposition for Ensembles over Multiple Synthetic Datasets
AISTATS 2025
Noise-Aware Differentially Private Variational Inference
AISTATS 2025
On Consistent Bayesian Inference from Synthetic Data
JMLR 2025
Noise-Aware Differentially Private Regression via Meta-Learning
NeurIPS 2024
Subsampling is not Magic: Why Large Batch Sizes Work for Differentially Private Stochastic Optimisation
ICML 2024
Individual Privacy Accounting with Gaussian Differential Privacy
ICLR 2023
Noise-Aware Statistical Inference with Differentially Private Synthetic Data
AISTATS 2023
Differentially Private Bayesian Inference for Generalized Linear Models
ICML 2021
Tight Differential Privacy for Discrete-Valued Mechanisms and for the Subsampled Gaussian Mechanism Using FFT
AISTATS 2021
Computing Tight Differential Privacy Guarantees Using FFT
AISTATS 2020
Learning Rate Adaptation for Differentially Private Learning
AISTATS 2020
Differentially Private Markov Chain Monte Carlo
NeurIPS 2019
Differentially private Bayesian learning on distributed data
NeurIPS 2017
Approximate Riemannian Conjugate Gradient Learning for Fixed-Form Variational Bayes
JMLR 2010