2 papers
cs.DS2024
Calibrated Recommendations for Users with Decaying Attention
Jon Kleinberg, Emily Ryu, Ãva Tardos
Recommendation systems capable of providing diverse sets of results are a focus of increasing importance, with motivations ranging from fairness to novelty and other aspects of opt…
cs.GT2024
Liquid Welfare Guarantees for No-Regret Learning in Sequential Budgeted Auctions
Giannis Fikioris, Ãva Tardos
We study the liquid welfare in sequential first-price auctions with budget-limited buyers. We focus on first-price auctions, which are increasingly commonly used in many settings,…