2 papers
cs.GT2025
Learning in Budgeted Auctions with Spacing Objectives
Giannis Fikioris, Robert Kleinberg, Yoav Kolumbus +3
In many repeated auction settings, participants care not only about how frequently they win but also how their winnings are distributed over time. This problem arises in various pr…
cs.LG2024
How to Boost Any Loss Function
Richard Nock, Yishay Mansour
Boosting is a highly successful ML-born optimization setting in which one is required to computationally efficiently learn arbitrarily good models based on the access to a weak lea…