Feb. 13, 2024, 5:44 a.m. | Yuepeng Yang Antares Chen Lorenzo Orecchia Cong Ma

cs.LG updates on arXiv.org arxiv.org

In this paper, we address the top-$K$ ranking problem with a monotone adversary. We consider the scenario where a comparison graph is randomly generated and the adversary is allowed to add arbitrary edges. The statistician's goal is then to accurately identify the top-$K$ preferred items based on pairwise comparisons derived from this semi-random comparison graph. The main contribution of this paper is to develop a weighted maximum likelihood estimator (MLE) that achieves near-optimal sample complexity, up to a $\log^2(n)$ factor, …

comparison cs.it cs.lg generated graph identify math.it math.st paper random ranking stat.ml stat.th

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