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cs.LG2026
Semantic Pareto-DQN: A Multi-Objective Reinforcement Learning Framework for Financial Anomaly Detection
Cláudio Lúcio do Val Lopes, Lucca Machado da Silva
Financial anomaly detection suffers from extreme class imbalance, causing traditional single-objective algorithms to exhibit ``fraud collapse'', defaulting to the majority class an…
cs.LG2026
Partition-Guided Distance Saliency: Bridging Decision and Objective Spaces in Many-Objective Optimization
Cláudio Lúcio do Val Lopes, Flávio VinÃcius Cruzeiro Martins, Elizabeth Fialho Wanner
Explainability in Many-Objective Optimization (MaO) is currently hindered by the escalating complexity of the Pareto front, which renders the relationship between high-dimensional…