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Showing 1 to 5 of 5 for “"Machine Learning Fairness"”.

  1. Discrimination, fairness and prediction in policing : fare evasion in New York City

    … is legally discriminatory. In this framework the fairness of a government policy is judged based on how different groups are treated by the process of carrying out the policy. Three elements must be examined: a comparison group that is treated fairly, discriminatory burden for the disadvantaged …

    mit Repository record for Discrimination, fairness and prediction in policing : fare evasion in New York City (opens in a new tab)

  2. Fairness for affective and wellbeing computing

    Recent advancements in machine learning (ML) as well as affective and wellbeing computing methodologies have enabled affective and wellbeing computing technologies to be increasingly used and integrated into daily human life. However, the problem of bias in machine-learning based tools and systems …

    cambridge Repository record for Fairness for affective and wellbeing computing (opens in a new tab)

  3. Towards a psychological science of neural network behaviour

    The pace of progress in machine learning is astounding. As a community, we have made great leaps forward across a variety of tasks, from complex vision challenges such as scene segmentation and object recognition, to striking language understanding capability and remarkably fluent text generation. …

    cambridge Repository record for Towards a psychological science of neural network behaviour (opens in a new tab)

  4. Machine Learning for Mobile Healthcare

    gmu

  5. Beyond traditional assumptions in fair machine learning

    … common assumptions underlying traditional machine learning approaches to fairness in consequential decision making. After challenging the validity of these assumptions in real-world applications, we propose ways to move forward when they are violated. First, we show that group fairness

    cambridge Repository record for Beyond traditional assumptions in fair machine learning (opens in a new tab)