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Found 4 papers, 1 papers with code
Locally Private Estimation with Public Features
Then we propose HistOfTree, an estimator that fully leverages the information contained in both public and private features.
Bagged Regularized $k$-Distances for Anomaly Detection
We consider the paradigm of unsupervised anomaly detection, which involves the identification of anomalies within a dataset in the absence of labeled examples.
Optimal Locally Private Nonparametric Classification with Public Data
Then, we present a novel approach, the locally differentially private classification tree, which attains the mini-max optimal convergence rate.
Frequency Principle in Deep Learning Beyond Gradient-descent-based Training
Frequency perspective recently makes progress in understanding deep learning.
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