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New algorithm learns two-sided platform parameters to optimize assortments

By PulseAugur Editorial · [3 sources] ·

Researchers have developed a novel data-driven algorithm for dynamic assortment problems on two-sided service platforms. This algorithm addresses the challenge of incomplete information by learning the choice-model parameters of both customers and sellers over time. The approach aims to optimize the platform's objective by minimizing regret, which measures revenue loss compared to an ideal scenario where all parameters are known. AI

IMPACT Introduces a novel algorithm for optimizing two-sided platforms, potentially improving efficiency in online marketplaces.

RANK_REASON The cluster contains an academic paper detailing a new algorithm and theoretical analysis.

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 3 sources. How we write summaries →

COVERAGE [3]

  1. arXiv cs.LG TIER_1 English(EN) · Jayashankar M. Swaminathan ·

    Data-Driven Dynamic Assortment in Online Platforms: Learning about Two Sides

    We study a dynamic assortment problem on a two-sided service platform with incomplete information and heterogeneous customers in a discrete-time setting. In each period, a customer arrives seeking service, and the platform chooses an assortment of sellers to display. The customer…

  2. arXiv stat.ML TIER_1 English(EN) · Rahul Roy, Nur Sunar, Jayashankar M. Swaminathan ·

    Data-Driven Dynamic Assortment in Online Platforms: Learning about Two Sides

    arXiv:2606.11118v1 Announce Type: cross Abstract: We study a dynamic assortment problem on a two-sided service platform with incomplete information and heterogeneous customers in a discrete-time setting. In each period, a customer arrives seeking service, and the platform chooses…

  3. arXiv stat.ML TIER_1 English(EN) · Jayashankar M. Swaminathan ·

    Data-Driven Dynamic Assortment in Online Platforms: Learning about Two Sides

    We study a dynamic assortment problem on a two-sided service platform with incomplete information and heterogeneous customers in a discrete-time setting. In each period, a customer arrives seeking service, and the platform chooses an assortment of sellers to display. The customer…

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