Incentive aware learning for large markets
Webof learning (see Lattimore and Szepesvári [LS20] for a textbook treatment). More speci˙cally, our three main contributions are: (i) We develop an incentive-aware learning objective—Subset Instability—that captures the distance of a market outcome from equilibrium. (ii) Using Subset Instability as a measure of WebWe design an incentive-aware learning objective that captures the distance of a market outcome from equilibrium. Using this objective, we analyze the complexity of learning as a function of preference structure, casting learning as …
Incentive aware learning for large markets
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WebAs a concrete application of the general incentive-aware learning framework, we will consider the auction setting where the designer/seller (he) simultaneously sells m items … http://epasto.org/
WebOct 14, 2024 · Abstract. Motivated by pricing in ad exchange markets, we consider the problem of robust learning of reserve prices against strategic buyers in repeated contextual second-price auctions. Buyers’ valuations for an item depend on the context that describes the item. However, the seller is not aware of the relationship between the context and ... WebOct 14, 2024 · In “Dynamic Incentive-Aware Learning: Robust Pricing in Contextual Auctions,” N. Golrezaei, A. Javanmard, and V. Mirrokni design effective learning algorithms with sublinear regret in such...
Weblearning stable market outcomes under uncertainty. Our primary setting is matching with transferable utilities, where the platform both matches agents and sets mone-tary … WebApr 10, 2024 · In this paper, we study such incentive-aware learning problem in a general setting and show that it is possible to approximately optimize the objective function under …
WebIn this paper, we study such incentive-aware learning problem in a general setting and show that it is possible to approximately optimize the objective function under two assumptions: (i) each individual agent is a "small" (part of the market); and (ii) there is a cost …
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