Federated Learning: Challenges, Methods, and Future Directions
Federated learning involves training statistical models over remote devices or siloed data centers, such as mobile phones or hospitals, while keeping data localized. Training in...
Publications
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719 publications
The diagnosis and management of non-alcoholic fatty liver disease: Practice Guideline by the American Association for the Study of Liver Diseases, American College of Gastroenterology, and the American Gastroenterological Association
These recommendations are based on the following: (1) a formal review and analysis of the recently published world literature on the topic [Medline search up to June 2011]; (2) ...
Report 9: Impact of non-pharmaceutical interventions (NPIs) to reduce COVID19 mortality and healthcare demand
The global impact of COVID-19 has been profound, and the public health threat it represents is the most serious seen in a respiratory virus since the 1918 H1N1 influenza pandemi...
Advances and Open Problems in Federated Learning
Federated learning (FL) is a machine learning setting where many clients (e.g. mobile devices or whole organizations) collaboratively train a model under the orchestration of a ...
Bayesian phylogenetic and phylodynamic data integration using BEAST 1.10
The Bayesian Evolutionary Analysis by Sampling Trees (BEAST) software package has become a primary tool for Bayesian phylogenetic and phylodynamic inference from genetic sequenc...
Comorbidity and its impact on 1590 patients with COVID-19 in China: a nationwide analysis
Background The coronavirus disease 2019 (COVID-19) outbreak is evolving rapidly worldwide. Objective To evaluate the risk of serious adverse outcomes in patients with COVID-19 b...
Distance-IoU Loss: Faster and Better Learning for Bounding Box Regression
Bounding box regression is the crucial step in object detection. In existing methods, while ℓn-norm loss is widely adopted for bounding box regression, it is not tailored to the...
Superconductivity of Metals and Alloys
Drawn from the author's introductory course at the University of Orsay, Superconductivity of Metals and Alloys is intended to explain the basic knowledge of superconductivity fo...
Effect size, confidence interval and statistical significance: a practical guide for biologists
Abstract Null hypothesis significance testing (NHST) is the dominant statistical approach in biology, although it has many, frequently unappreciated, problems. Most importantly,...