30 citations · 51 across the 6 of their papers we have counts for
7 papers
FaiREE: Fair Classification with Finite-Sample and Distribution-Free Guarantee
Puheng Li, James Zou, Linjun Zhang
Algorithmic fairness plays an increasingly critical role in machine learning research. Several group fairness notions and algorithms have been proposed. However, the fairness guara…
WeightedSHAP: analyzing and improving Shapley based feature attributions
Yongchan Kwon, James Zou
Shapley value is a popular approach for measuring the influence of individual features. While Shapley feature attribution is built upon desiderata from game theory, some of its con…
Signal to noise in matching markets
S. Matthew Weinberg, James Zou
In many matching markets, one side "applies" to the other, and these applications are often expensive and time-consuming (e.g. students applying to college). It is tempting to thin…
Contingent Payment Mechanisms for Resource Utilization
Hongyao Ma, Reshef Meir, David C. Parkes +1
We introduce the problem of assigning resources to improve their utilization. The motivation comes from settings where agents have uncertainty about their own values for using a re…
How much does your data exploration overfit? Controlling bias via information usage
Daniel Russo, James Zou
Modern data is messy and high-dimensional, and it is often not clear a priori what are the right questions to ask. Instead, the analyst typically needs to use the data to search fo…
Incentive-Compatible Experimental Design
Panos Toulis, David C. Parkes, Elery Pfeffer +1
We consider the design of experiments to evaluate treatments that are administered by self-interested agents, each seeking to achieve the highest evaluation and win the experiment.…
Mechanism Design for Time Critical and Cost Critical Task Execution via Crowdsourcing
Swaprava Nath, Pankaj Dayama, Dinesh Garg +2
An exciting application of crowdsourcing is to use social networks in complex task execution. In this paper, we address the problem of a planner who needs to incentivize agents wit…