FERERO: A Flexible Framework for Preference-Guided Multi-Objective Learning Lisha Chen

Neural Information Processing Systems 

Finding specific preference-guided Pareto solutions that represent different tradeoffs among multiple objectives is critical yet challenging in multi-objective problems. Existing methods are restrictive in preference definitions and/or their theoretical guarantees.

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