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结合协变量与稀疏内在得分的实体排序AI 解读

This paper addresses the item ranking problem with associated covariates, focusing on scenarios where the preference scores can not be fully explained by covariates, and the remaining intrinsic scores are sparse. Specifically, we extend the pioneering Bradley-Terry-Luce (BTL) model by incorporating covariate information and considering sparse individual intrinsic scores. Our work introduces novel model identification conditions and examines the statistical rates of the…

混合成员模型中混合概率与排序的统计推断AI 解读

Network data is prevalent in numerous big data applications, including economics and health networks, where understanding the latent structure of the network is of prime importance. In this paper, we model the network using the Degree-Corrected Mixed Membership (DCMM) model. In the DCMM model, for each node i, there exists a membership vector πi=(πi(1),πi(2),…,πi(K)), where πi(k) denotes the weight that node i puts in community k. We derive a novel finite-sample expansion…