2 papers
cs.LG2025
Conformal Prediction for Privacy-Preserving Machine Learning
Alexander David Balinsky, Dominik Krzeminski, Alexander Balinsky
We investigate the integration of Conformal Prediction (CP) with supervised learning on deterministically encrypted data, aiming to bridge the gap between rigorous uncertainty quan…
cs.LG2025
When Can We Reuse a Calibration Set for Multiple Conformal Predictions?
A. A. Balinsky, A. D. Balinsky
Reliable uncertainty quantification is crucial for the trustworthiness of machine learning applications. Inductive Conformal Prediction (ICP) offers a distribution-free framework f…