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constrained optimization

topic2 events
papersTODAY 04:00 UTC

Paper Suggests Analyzing Fairness Through Utilities Instead of Constrained Policies

The authors argue that fairness criteria which restrict a predictor or policy can produce unwanted side effects, especially when the policy is optimized under those constraints. They propose instead examining fairness directly through utility functions, and offer initial steps toward fairness objectives that avoid those drawbacks. The work is a revised cross-listing on arXiv in machine learning.

fairness/machine-learning/research/arxiv
papersTODAY 04:00 UTC

Projection-Free Methods for Stochastic Constrained Compositional Optimization

A new arXiv paper develops projection-free algorithms for stochastic optimization problems whose objectives are nested compositions of smooth functions over a closed convex decision set. The work targets the multi-level compositional setting, where gradients must be estimated through several layers of functions. It aims to avoid costly projection steps while still handling constraints.

optimization/arxiv/theory/algorithms