arXiv cs.AI
· Papers
Efficient Online Proportional Sampling with Applications to Smoothed Online Learning
arXiv:2607.10963v1 Announce Type: cross Abstract: We study the problem of efficient online proportional sampling from a high-dimensional domain under a $sigma$-smoothed adversary, where the sampling distribution is induced by a dynamically evolving weight function defined over a sequence of piecewise-structured partit