In this note, we consider the problem of robust learning mixtures of linear regressions. We connect mixtures of linear regressions and mixtures of Gaussians with a simple thresholding, so that a quasi-polynomial time algorithm can be obtained under some mild separation condition. This algorithm has significantly better robustness than the previous result.

翻译：本文探讨了线性回归混合模型的鲁棒学习问题。我们通过简单阈值化将线性回归混合模型与高斯混合模型联系起来，使得在温和分离条件下能够得到拟多项式时间算法。该算法相比先前结果具有显著更强的鲁棒性。