Corruption-tolerant Algorithms for Generalized Linear Models

This paper presents SVAM (Sequential Variance-Altered MLE), a unified framework for learning generalized linear models under adversarial label corruption in training data. SVAM extends to tasks such as least squares regression, logistic regression, and gamma regression, whereas many existing works on learning with label corruptions focus only on least squares regression. SVAM is based on a novel variance reduction technique that may be of independent interest and works by iteratively solving weighted MLEs over variance-altered versions of the GLM objective. SVAM offers provable model recovery guarantees superior to the state-of-the-art for robust regression even when a constant fraction of training labels are adversarially corrupted. SVAM also empirically outperforms several existing problem-specific techniques for robust regression and classification. Code for SVAM is available at https://github.com/purushottamkar/svam/Comment: 46 pages, 5 figures, to appear in the 31st AAAI Conference on Artificial Intelligence (AAAI), 202

Dyssynchrony in obese subjects without a history of cardiac disease using velocity vector imaging

Abstract Aim: To examine the occurrence of intra-left ventricular (LV) dyssynchrony in obese versus non-obese subjects without known cardiac disease using velocity vector imaging (VVI). Methods: One hundred ninety consecutive subjects with no known cardiac disease had their echocardiograms analyzed using VVI after excluding subjects with QRS duration \u3e120ms or LV ejection fraction (LVEF) \u3c55%. Study subjects were divided into two groups based on body mass index (BMI): obese (BMI \u3e30 kg/m2) and non-obese (BMI \u3c30 kg\u3e/m2). Results: The final cohort included 136 subjects (74 were obese), 32% female and mean age 55 + 16 years. Occurrence of intra LV dyssynchrony was higher in the obese compared to non-obese group. Conclusions: There was an increased prevalence of intra LV dyssynchrony in obese subjects, especially longitudinal and radial dyssynchrony. This dyssynchrony may signal a mechanism by which obesity predisposes to the development of heart failure