no code implementations • 22 Feb 2023 • Maria-Florina Balcan, Hedyeh Beyhaghi
We advance a recently flourishing line of work at the intersection of learning theory and computational economics by studying the learnability of two classes of mechanisms prominent in economics, namely menus of lotteries and two-part tariffs.
no code implementations • 28 Feb 2022 • Saba Ahmadi, Hedyeh Beyhaghi, Avrim Blum, Keziah Naggita
A key technical challenge of this problem is the non-monotonicity of social welfare in the set of target levels, i. e., adding a new target level may decrease the total amount of improvement as it may get easier for some agents to improve.
no code implementations • 28 Feb 2022 • Saba Ahmadi, Hedyeh Beyhaghi, Avrim Blum, Keziah Naggita
For the general discrete model, we give an efficient algorithm for the problem of maximizing the number of true positives subject to no false positives, and show how to extend this to a partial-information learning setting.
no code implementations • 4 Aug 2020 • Saba Ahmadi, Hedyeh Beyhaghi, Avrim Blum, Keziah Naggita
The classical Perceptron algorithm provides a simple and elegant procedure for learning a linear classifier.