1 code implementation • 30 Aug 2018 • Jacob Nogas, Shehroz S. Khan, Alex Mihailidis
Human falls rarely occur; however, detecting falls is very important from the health and safety perspective.
no code implementations • 19 May 2019 • Shehroz S. Khan, Jacob Nogas, Alex Mihailidis
In this paper, we take an alternate philosophy to detect falls in the absence of their training data, by training the classifier on only the normal activities (that are available in abundance) and identifying a fall as an anomaly.
no code implementations • 22 Mar 2021 • Joseph Jay Williams, Jacob Nogas, Nina Deliu, Hammad Shaikh, Sofia S. Villar, Audrey Durand, Anna Rafferty
We therefore use our case study of the ubiquitous two-arm binary reward setting to empirically investigate the impact of using Thompson Sampling instead of uniform random assignment.
no code implementations • 15 Dec 2021 • Tong Li, Jacob Nogas, Haochen Song, Harsh Kumar, Audrey Durand, Anna Rafferty, Nina Deliu, Sofia S. Villar, Joseph J. Williams
TS-PostDiff takes a Bayesian approach to mixing TS and Uniform Random (UR): the probability a participant is assigned using UR allocation is the posterior probability that the difference between two arms is 'small' (below a certain threshold), allowing for more UR exploration when there is little or no reward to be gained.
no code implementations • 10 Aug 2022 • Angela Zavaleta-Bernuy, Qi Yin Zheng, Hammad Shaikh, Jacob Nogas, Anna Rafferty, Andrew Petersen, Joseph Jay Williams
Adaptive experiments can increase the chance that current students obtain better outcomes from a field experiment of an instructional intervention.