This white paper is a response to the "AI Accountability Policy Request ...
We study the problem of fairly allocating indivisible goods (positively
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We propose a novel data-driven framework for algorithmic recourse that o...
We study the problem of allocating indivisible chores among agents with
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Fair allocation of indivisible goods is a well-explored problem.
Traditi...
We study the problem of fairly allocating a set of indivisible goods amo...
Peer review cannot work unless qualified and interested reviewers are
as...
We study the problem of fairly allocating a set of indivisible goods amo...
We study fair allocation of indivisible goods when agents have matroid r...
Explaining the decisions of black-box models has been a central theme in...
Scientific advancement requires effective peer review. Papers should be
...
Equilibrium computation in markets usually considers settings where play...
Black-box machine learning models are used in critical decision-making
d...
Complex black-box machine learning models are regularly used in critical...
Combinatorial Game Theory (CGT) is a branch of game theory that has deve...
In this paper, we present new results on the fair and efficient allocati...
We examine the problem of assigning plots of land to prospective buyers ...
In this paper, we introduce and analyze new envy-based fairness concepts...
Can we trust black-box machine learning with its decisions? Can we trust...
The past few years have seen several works establishing PAC frameworks f...
Influence maximization is a widely used model for information disseminat...
A community needs to be partitioned into disjoint groups; each community...
The state of Singapore operates a national public housing program, accou...
In this work we focus on the following question: how important was the i...