2 papers
stat.ML2023
Conformal Prediction for Federated Uncertainty Quantification Under Label Shift
Vincent Plassier, Mehdi Makni, Aleksandr Rubashevskii +2
Federated Learning (FL) is a machine learning framework where many clients collaboratively train models while keeping the training data decentralized. Despite recent advances in FL…
cs.LG2023
Scalable Batch Acquisition for Deep Bayesian Active Learning
Aleksandr Rubashevskii, Daria Kotova, Maxim Panov
In deep active learning, it is especially important to choose multiple examples to markup at each step to work efficiently, especially on large datasets. At the same time, existing…