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Found 5 papers, 0 papers with code
One-bit Submission for Locally Private Quasi-MLE: Its Asymptotic Normality and Limitation
Local differential privacy~(LDP) is an information-theoretic privacy definition suitable for statistical surveys that involve an untrusted data curator.
Differentially Private Variational Autoencoders with Term-wise Gradient Aggregation
This paper studies how to learn variational autoencoders with a variety of divergences under differential privacy constraints.
Locally Private Distributed Reinforcement Learning
To the best of our knowledge, this is the first work that actualizes distributed reinforcement learning under LDP.
Lightweight Lipschitz Margin Training for Certified Defense against Adversarial Examples
Lipschitz margin training (LMT) is a scalable certified defense, but it can also only achieve small robustness due to over-regularization.
Reading-Time Annotations for ``Balanced Corpus of Contemporary Written Japanese''
The Dundee Eyetracking Corpus contains eyetracking data collected while native speakers of English and French read newspaper editorial articles.
