Data Market Design through Deep Learning

arXiv:2310.20096 · cs.GT, cs.AI · Submitted 2023-10-31 · Read on arXiv

cs.GT, cs.AI

Submitted: 2023-10-31

Updated: 2026-09-02

Code: https://github.com/saisrivatsan/deep-data-markets

Terminology

• Regret — 23× in this paper · explained in 3 episodes
• Alignment — 4× in this paper · explained in 1 episode
• Loss Function — 3× in this paper · explained in 2 episodes
• Action Space — 1× in this paper · explained in 1 episode
• Activation Function — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 2 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• Transformer — 1× in this paper · explained in 2 episodes

Sources

• Towards Data Auctions with Externalities
• Selling Information in Competitive Environments
• Selling Information Through Consulting
• ProportionNet: Balancing Fairness and Revenue for Auction Design with Deep Learning
• Deep Learning for Two-Sided Matching
• Learning Truthful, Efficient, and Welfare Maximizing Auction Rules

Related papers

• Exact Regret Frontiers and Externality Scheduling in Centralized Serial-Dictatorship Bandits
• In-Context Credit Assignment via the Core
• Breaking 1/epsilon Barrier in Quantum Zero-Sum Games: Generalizing Metric Subregularity for Spectraplexes
• Enhancing Affine Maximizer Auctions with Correlation-Aware Payment
• LLM Bidders Preserve the Mechanism-Level Orderings of Human Bidders
• Towards Performatively Stable Equilibria in Decision-Dependent Games for Arbitrary Data Distribution Maps