An aggregate NTU stability concept using one-sided money burning decentralizes stable matchings in type-based markets and extends to a random utility model with proven existence, uniqueness, and convergent algorithm.
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Two polynomial-time algorithms are proposed for multilevel fair allocation under matroid-rank preferences, one generic with efficiency and fairness guarantees and one extending General Yankee Swap with efficiency guarantees and strong practical fairness.
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Aggregate Stable Matching with Money Burning
An aggregate NTU stability concept using one-sided money burning decentralizes stable matchings in type-based markets and extends to a random utility model with proven existence, uniqueness, and convergent algorithm.
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Multilevel Fair Allocation with Matroid-Rank Preferences
Two polynomial-time algorithms are proposed for multilevel fair allocation under matroid-rank preferences, one generic with efficiency and fairness guarantees and one extending General Yankee Swap with efficiency guarantees and strong practical fairness.