3 citations · 6 across the 5 of their papers we have counts for
6 papers
Fair and Welfare-Efficient Constrained Multi-matchings under Uncertainty
Elita Lobo, Justin Payan, Cyrus Cousins +1
We study fair allocation of constrained resources, where a market designer optimizes overall welfare while maintaining group fairness. In many large-scale settings, utilities are n…
Into the Unknown: Assigning Reviewers to Papers with Uncertain Affinities
Cyrus Cousins, Justin Payan, Yair Zick
A successful peer review process requires that qualified and interested reviewers are assigned to each paper. Most automated reviewer assignment approaches estimate a real-valued a…
Graphical House Allocation
Hadi Hosseini, Justin Payan, Rik Sengupta +2
The classical house allocation problem involves assigning houses (or items) to agents according to their preferences. A key criterion in such problems is satisfying some fa…
Relaxations of Envy-Freeness Over Graphs
Justin Payan, Rik Sengupta, Vignesh Viswanathan
When allocating a set of indivisible items among agents, the ideal condition of envy-freeness cannot always be achieved. Envy-freeness up to any good (EFX), and envy-freeness with…
Towards Realistic Single-Task Continuous Learning Research for NER
Justin Payan, Yuval Merhav, He Xie +4
There is an increasing interest in continuous learning (CL), as data privacy is becoming a priority for real-world machine learning applications. Meanwhile, there is still a lack o…
I Will Have Order! Optimizing Orders for Fair Reviewer Assignment
Justin Payan, Yair Zick
We present fast, fair, flexible, and welfare efficient algorithms for assigning reviewers to submitted conference papers. Our approaches extend picking sequence mechanisms, standar…