atlas

Research map / Learning theory and algorithms / Fairness

Fair Continuous Resource Allocation with Equality of Impact

NeurIPS 2025 · Learning theory and algorithms › Fairness · approach: Fair allocation and selection · 0 citations (OpenAlex)

Read the paperCheck your idea against 108,967 papers

AI-extracted summary. Written by AI from the paper's abstract only. Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.

Develops continuous resource allocation strategies that satisfy equality of impact, a generalization of equality of opportunity, for fairness judged by allocation impact rather than allocation thresholds.

Problem

Fair resource allocation in social settings where fairness is judged by the impact of allocation decisions rather than minimum or maximum thresholds on the allocations themselves.

Approach

Extends the impact-based fairness literature to continuous resource allocation by defining equality of impact, a generalization of equality of opportunity, and deriving allocation strategies that satisfy it.

Experimental setup

Builds on: equality of opportunity

Closest papers by meaning

Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.

Open scime draft

Get the next scime Dispatch and a monthly field update

Free. We send a confirmation link first; every email has a one-click unsubscribe. Privacy