AINeutralarXiv – CS AI · 9h ago6/10
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A Resilience Framework for Bi-Criteria Combinatorial Optimization with Bandit Feedback
Researchers introduce a resilience framework for bi-criteria combinatorial optimization under noisy conditions, extending bandit feedback algorithms from single-objective to multi-objective settings. The framework achieves sublinear regret bounds without requiring structural assumptions like linearity or submodularity, with potential applications to constrained optimization problems in machine learning and algorithmic decision-making.