Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
A review on fairness in machine learning
An increasing number of decisions regarding the daily lives of human beings are being
controlled by artificial intelligence and machine learning (ML) algorithms in spheres ranging …
controlled by artificial intelligence and machine learning (ML) algorithms in spheres ranging …
The evolution of distributed systems for graph neural networks and their origin in graph processing and deep learning: A survey
Graph neural networks (GNNs) are an emerging research field. This specialized deep
neural network architecture is capable of processing graph structured data and bridges the …
neural network architecture is capable of processing graph structured data and bridges the …
A snapshot of the frontiers of fairness in machine learning
A snapshot of the frontiers of fairness in machine learning Page 1 82 COMMUNICATIONS OF
THE ACM | MAY 2020 | VOL. 63 | NO. 5 review articles ILL US TRA TION B Y JUS TIN METZ …
THE ACM | MAY 2020 | VOL. 63 | NO. 5 review articles ILL US TRA TION B Y JUS TIN METZ …
The frontiers of fairness in machine learning
The last few years have seen an explosion of academic and popular interest in algorithmic
fairness. Despite this interest and the volume and velocity of work that has been produced …
fairness. Despite this interest and the volume and velocity of work that has been produced …
Fair preprocessing: towards understanding compositional fairness of data transformers in machine learning pipeline
In recent years, many incidents have been reported where machine learning models
exhibited discrimination among people based on race, sex, age, etc. Research has been …
exhibited discrimination among people based on race, sex, age, etc. Research has been …
Predict responsibly: improving fairness and accuracy by learning to defer
In many machine learning applications, there are multiple decision-makers involved, both
automated and human. The interaction between these agents often goes unaddressed in …
automated and human. The interaction between these agents often goes unaddressed in …
Discovering fair representations in the data domain
Interpretability and fairness are critical in computer vision and machine learning
applications, in particular when dealing with human outcomes, eg inviting or not inviting for a …
applications, in particular when dealing with human outcomes, eg inviting or not inviting for a …
Towards unbiased and accurate deferral to multiple experts
Machine learning models are often implemented in cohort with humans in the pipeline, with
the model having an option to defer to a domain expert in cases where it has low confidence …
the model having an option to defer to a domain expert in cases where it has low confidence …
Fairness under composition
Algorithmic fairness, and in particular the fairness of scoring and classification algorithms,
has become a topic of increasing social concern and has recently witnessed an explosion of …
has become a topic of increasing social concern and has recently witnessed an explosion of …
Should fairness be a metric or a model? A model-based framework for assessing bias in machine learning pipelines
Fairness measurement is crucial for assessing algorithmic bias in various types of machine
learning (ML) models, including ones used for search relevance, recommendation …
learning (ML) models, including ones used for search relevance, recommendation …