论文标题
洗牌的总正方形
Shuffled total least squares
论文作者
论文摘要
带有洗牌标签和带有嘈杂潜在设计矩阵的线性回归在许多对应恢复问题中出现。我们提出了一种总体最小二乘的方法来估计基本真实排列的问题，并为标准化procrustes估算器的二次损失提供了上限。我们还提供了一种迭代算法来近似估计器并在模拟数据上演示其性能。
Linear regression with shuffled labels and with a noisy latent design matrix arises in many correspondence recovery problems. We propose a total least-squares approach to the problem of estimating the underlying true permutation and provide an upper bound to the normalized Procrustes quadratic loss of the estimator. We also provide an iterative algorithm to approximate the estimator and demonstrate its performance on simulated data.
