A new algorithm and a discussion about visualization for logistic reduced rank regression
M de Rooij - Behaviormetrika, 2024 - Springer
Logistic reduced rank regression is a useful data analysis tool when we have multiple binary
response variables and a set of predictors. In this paper, we describe logistic reduced rank …
response variables and a set of predictors. In this paper, we describe logistic reduced rank …
Privacy-Preserving Logistic Regression Training on Large Datasets
J Chiang - arXiv preprint arXiv:2406.13221, 2024 - arxiv.org
Privacy-preserving machine learning is one class of cryptographic methods that aim to
analyze private and sensitive data while keeping privacy, such as homomorphic logistic …
analyze private and sensitive data while keeping privacy, such as homomorphic logistic …
Improving robustness to corruptions with multiplicative weight perturbations
Deep neural networks (DNNs) excel on clean images but struggle with corrupted ones.
Incorporating specific corruptions into the data augmentation pipeline can improve …
Incorporating specific corruptions into the data augmentation pipeline can improve …
MM Algorithms for Statistical Estimation in Quantile Regression
Y Cheng, AYC Kuk - arXiv preprint arXiv:2407.12348, 2024 - arxiv.org
Quantile regression is a robust and practically useful way to efficiently model quantile
varying correlation and predict varied response quantiles of interest. This article constructs …
varying correlation and predict varied response quantiles of interest. This article constructs …
LFFR: Logistic Function For (multi-output) Regression
J Chiang - arXiv preprint arXiv:2407.21187, 2024 - arxiv.org
In this manuscript, we extend our previous work on privacy-preserving regression to address
multi-output regression problems using data encrypted under a fully homomorphic …
multi-output regression problems using data encrypted under a fully homomorphic …
LFFR: Logistic Function For (single-output) Regression
J Chiang - arXiv preprint arXiv:2407.09955, 2024 - arxiv.org
Privacy-preserving regression in machine learning is a crucial area of research, aimed at
enabling the use of powerful machine learning techniques while protecting individuals' …
enabling the use of powerful machine learning techniques while protecting individuals' …