Mitigating Confounding Bias in Recommendation via Information Bottleneck

2021 ◽  
Author(s):  
Dugang Liu ◽  
Pengxiang Cheng ◽  
Hong Zhu ◽  
Zhenhua Dong ◽  
Xiuqiang He ◽  
...  
2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Erik Buhmann ◽  
Sascha Diefenbacher ◽  
Engin Eren ◽  
Frank Gaede ◽  
Gregor Kasieczka ◽  
...  

AbstractAccurate simulation of physical processes is crucial for the success of modern particle physics. However, simulating the development and interaction of particle showers with calorimeter detectors is a time consuming process and drives the computing needs of large experiments at the LHC and future colliders. Recently, generative machine learning models based on deep neural networks have shown promise in speeding up this task by several orders of magnitude. We investigate the use of a new architecture—the Bounded Information Bottleneck Autoencoder—for modelling electromagnetic showers in the central region of the Silicon-Tungsten calorimeter of the proposed International Large Detector. Combined with a novel second post-processing network, this approach achieves an accurate simulation of differential distributions including for the first time the shape of the minimum-ionizing-particle peak compared to a full Geant4 simulation for a high-granularity calorimeter with 27k simulated channels. The results are validated by comparing to established architectures. Our results further strengthen the case of using generative networks for fast simulation and demonstrate that physically relevant differential distributions can be described with high accuracy.


2019 ◽  
Vol 81 (1-2) ◽  
pp. 81-86
Author(s):  
Pierre Koskas ◽  
Mouna Romdhani ◽  
Olivier Drunat

As commonly happens in epidemiological research, none of the reported studies were totally free of methodological problems. Studies have considered the influence of social relationships on dementia, but the mechanisms underlying these associations are not perfectly understood. We look at the possible impact of selection bias. For their first memory consultation, patients may come alone or accompanied by a relative. Our objective is to better understand the impact of this factor by retrospective follow-up of geriatric memory outpatients over several years. All patients over 70 who were referred to Bretonneau Memory Clinic for the first time, between January 2006 and 2018, were included in the study. The patients who came alone formed group 1, the others, whatever type of relative accompanied them, formed group 2. We compared the Mini-Mental State Examination (MMSE) scores of patients; and for all patients who came twice for consultation with at least a 60-day interval, we compared their first MMSE with the MMSE performed at the second consultation. In total, 2,935 patients were included, aged 79.7 ± 8.4 years. Six hundred and twenty-five formed group 1 and 2,310 group 2. We found a significant difference in MMSE scores between the 2 groups of patients; and upon second consultation in group 2, but that difference was minor in group 1. Our finding of a possible confounding factor underlines the complexity of choosing comparison groups in order to minimize selection bias while maintaining clinical relevance.


2021 ◽  
Author(s):  
Morten Ostergaard Nielsen ◽  
Jan Ostergaard ◽  
Jesper Jensen ◽  
Zheng-Hua Tan

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