output
20092026
most citedImproving fairness in machine learning systems: What do industry practitioners need?

758 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

collaborating institutions
Showing 2019Show all

5 papers · 1 filter

cs.LG2019★ 17 cited

Scalable Hierarchical Clustering with Tree Grafting

Nicholas Monath, Ari Kobren, Akshay Krishnamurthy +2

We introduce Grinch, a new algorithm for large-scale, non-greedy hierarchical clustering with general linkage functions that compute arbitrary similarity between two point sets. Th…

cs.CR2019★ 139 cited

Decentralized & Collaborative AI on Blockchain

Justin D. Harris, Bo Waggoner

Machine learning has recently enabled large advances in artificial intelligence, but these tend to be highly centralized. The large datasets required are generally proprietary; pre…

cs.GT2019★ 50 cited

Truthful Aggregation of Budget Proposals

Rupert Freeman, David M. Pennock, Dominik Peters +1

We consider a participatory budgeting problem in which each voter submits a proposal for how to divide a single divisible resource (such as money or time) among several possible al…

cs.GT2019★ 2 cited

The Perils of Exploration under Competition: A Computational Modeling Approach

Guy Aridor, Kevin Liu, Aleksandrs Slivkins +1

We empirically study the interplay between exploration and competition. Systems that learn from interactions with users often engage in exploration: making potentially suboptimal d…

cs.HC2019★ 758 cited

Improving fairness in machine learning systems: What do industry practitioners need?

Kenneth Holstein, Jennifer Wortman Vaughan, Hal Daumé +2

The potential for machine learning (ML) systems to amplify social inequities and unfairness is receiving increasing popular and academic attention. A surge of recent work has focus…