40 citations · 65 across the 9 of their papers we have counts for
10 papers
AI-Assisted Decision Making with Human Learning
Gali Noti, Kate Donahue, Jon Kleinberg +1
AI systems increasingly support human decision-making. In many cases, despite the algorithm's superior performance, the final decision remains in human hands. For example, an AI ma…
Decongestion by Representation: Learning to Improve Economic Welfare in Marketplaces
Omer Nahum, Gali Noti, David Parkes +1
Congestion is a common failure mode of markets, where consumers compete inefficiently on the same subset of goods (e.g., chasing the same small set of properties on a vacation rent…
Learning When to Advise Human Decision Makers
Gali Noti, Yiling Chen
Artificial intelligence (AI) systems are increasingly used for providing advice to facilitate human decision making in a wide range of domains, such as healthcare, criminal justice…
From Behavioral Theories to Econometrics: Inferring Preferences of Human Agents from Data on Repeated Interactions
Gali Noti
We consider the problem of estimating preferences of human agents from data of strategic systems where the agents repeatedly interact. Recently, it was demonstrated that a new esti…
Bid Prediction in Repeated Auctions with Learning
Gali Noti, Vasilis Syrgkanis
We consider the problem of bid prediction in repeated auctions and evaluate the performance of econometric methods for learning agents using a dataset from a mainstream sponsored s…
Neural Networks for Predicting Human Interactions in Repeated Games
Yoav Kolumbus, Gali Noti
We consider the problem of predicting human players' actions in repeated strategic interactions. Our goal is to predict the dynamic step-by-step behavior of individual players in p…
ERA: A Framework for Economic Resource Allocation for the Cloud
Moshe Babaioff, Yishay Mansour, Noam Nisan +7
Cloud computing has reached significant maturity from a systems perspective, but currently deployed solutions rely on rather basic economics mechanisms that yield suboptimal alloca…
A "Quantal Regret" Method for Structural Econometrics in Repeated Games
Noam Nisan, Gali Noti
We suggest a general method for inferring players' values from their actions in repeated games. The method extends and improves upon the recent suggestion of (Nekipelov et al., EC…
Behavior-Based Machine-Learning: A Hybrid Approach for Predicting Human Decision Making
Gali Noti, Effi Levi, Yoav Kolumbus +1
A large body of work in behavioral fields attempts to develop models that describe the way people, as opposed to rational agents, make decisions. A recent Choice Prediction Competi…
An Experimental Evaluation of Regret-Based Econometrics
Noam Nisan, Gali Noti
Using data obtained in a controlled ad-auction experiment that we ran, we evaluate the regret-based approach to econometrics that was recently suggested by Nekipelov, Syrgkanis, an…