Tag: safe
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Safe-EF: Error Feedback for Nonsmooth Constrained Optimization
Safe-EF: Error Feedback for Nonsmooth Constrained Optimization arXiv:2505.06053v1 Announce Type: cross Abstract: Federated learning faces severe communication bottlenecks due to the high dimensionality of model updates. Communication compression with contractive compressors (e.g., Top-K) is often preferable in practice but can degrade performance without proper handling. Error feedback (EF) mitigates such issues but has been largely…
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Probabilistic Shielding for Safe Reinforcement Learning
Probabilistic Shielding for Safe Reinforcement Learning arXiv:2503.07671v1 Announce Type: new Abstract: In real-life scenarios, a Reinforcement Learning (RL) agent aiming to maximise their reward, must often also behave in a safe manner, including at training time. Thus, much attention in recent years has been given to Safe RL, where an agent aims to learn an…
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Exact characterization of {epsilon}-Safe Decision Regions for exponential family distributions and Multi Cost SVM approximation
Exact characterization of {epsilon}-Safe Decision Regions for exponential family distributions and Multi Cost SVM approximation arXiv:2501.17731v1 Announce Type: new Abstract: Probabilistic guarantees on the prediction of data-driven classifiers are necessary to define models that can be considered reliable. This is a key requirement for modern machine learning in which the goodness of a system is…