Optimization
Preference-based Pure Exploration
Neural Information Processing Systems
We study the preference-based pure exploration problem for bandits with vector-valued rewards.
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Let the Flows T ell: Solving Graph Combinatorial Optimization Problems with GFlowNets
Neural Information Processing Systems
GFlowNet policies can efficiently find high-quality solutions.
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AGloballyOptimalPortfolioform-SparseSharpe RatioMaximization
Neural Information Processing Systems
In modern portfolio management, one may require anm-sparse (no more thanm active assets) portfolio to save managerial and financial costs.
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Sample-EfficientOptimizationintheLatentSpaceof DeepGenerativeModelsviaWeightedRetraining
Neural Information Processing Systems
Unfortunately, many real-world problems of practical interest have these characteristics.
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