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基于最大均值差异的通用稳健回归AI 解读

Abstract Many modern datasets are collected automatically and are thus easily contaminated by outliers. This has led to a renewed interest in robust estimation, including new notions of robustness such as robustness to adversarial contamination of the data. However, most robust estimation methods are designed for a specific model. Notably, many methods were proposed recently to obtain robust estimators in linear models, or generalized linear models, and a few were developed…

用于全局随机优化的粒子滤波算法AI 解读

Summary We introduce a new online algorithm for expected loglikelihood maximization in situations where the objective function is multimodal or has saddle points. The key element underpinning the algorithm is a probability distribution that concentrates on the target parameter value as the sample size increases and can be efficiently estimated by means of a standard particle filter algorithm. This distribution depends on a learning rate, such that the faster the learning…