3 papers
cs.LG2026
EVEREST: An Evidential, Tail-Aware Transformer for Rare-Event Time-Series Forecasting
Antanas Zilinskas, Robert N. Shorten, Jakub Marecek
Forecasting rare events in multivariate time-series data is challenging due to severe class imbalance, long-range dependencies, and distributional uncertainty. We introduce EVEREST…
cs.LG2025
humancompatible.train: Implementing Optimization Algorithms for Stochastically-Constrained Stochastic Optimization Problems
Andrii Kliachkin, Jana Lepšová, Gilles Bareilles +1
There has been a considerable interest in constrained training of deep neural networks (DNNs) recently for applications such as fairness and safety. Several toolkits have been prop…
cs.LG2025
Benchmarking Stochastic Approximation Algorithms for Fairness-Constrained Training of Deep Neural Networks
Andrii Kliachkin, Jana Lepšová, Gilles Bareilles +1
The ability to train Deep Neural Networks (DNNs) with constraints is instrumental in improving the fairness of modern machine-learning models. Many algorithms have been analysed in…