In this talk, Professor Daniel L. Gardner will discuss his recent book, Thresholds of Digital Gameplay(MIT Press), and current ongoing research. The book presents an analytical lens calibrated by peripheral-to-gameplay interfaces, interactions, infrastructures, and inequities.
Data-driven machine learning methods are making advances in many long-standing problems in robotics, including grasping, legged locomotion, perception, and more. There are, however, robotics applications for which data-driven methods are less effective. Data acquisition can be expensive, time consuming, or dangerous -- to the surrounding workspace, humans in the workspace, or the robot itself.
This free event is open only to members of the University of Cambridge (and affiliated institutes). Please be aware that we are unable to offer consultations outside clinic hours.
If you would like to participate, please sign up as we will not be able to offer a consultation otherwise. Please sign up through the following link: https://forms.gle/YxfR9eZFd2oD7C886. Sign-up is possible from July 30 midday (12pm) until August 3 midday or until we reach full capacity, whichever is earlier. If you successfully signed up, we will confirm your appointment by August 5 midday.
This free event is open only to members of the University of Cambridge (and affiliated institutes). Please be aware that we are unable to offer consultations outside clinic hours.
Professor Michael Elliott, University of Michigan School of Public Health
Longitudinal data has become a major part of the landscape for clinical and epidemiological research. While variance is typically understood as nuisance – the “noise” in “signal-to-noise” – there is increasing evidence that underlying variability in subject-level measures over time may also be important in predicting future health outcomes of interest.
