Zobrazeno 1 - 10
of 261
pro vyhledávání: '"Barnett, Ian"'
Autor:
Ren, Benny, Barnett, Ian, Shou, Haochang, Rubin, Jeremy, Zhu, Hongxiao, Conway, Terry, Cain, Kelli, Saelens, Brian, Glanz, Karen, Sallis, James, Morris, Jeffrey S.
In the age of digital healthcare, passively collected physical activity profiles from wearable sensors are a preeminent tool for evaluating health outcomes. In order to fully leverage the vast amounts of data collected through wearable accelerometers
Externí odkaz:
http://arxiv.org/abs/2411.12585
Recent advances in machine learning have significantly improved prediction accuracy in various applications. However, ensuring the calibration of probabilistic predictions remains a significant challenge. Despite efforts to enhance model calibration,
Externí odkaz:
http://arxiv.org/abs/2408.08998
Finite sample inference for Cox models is an important problem in many settings, such as clinical trials. Bayesian procedures provide a means for finite sample inference and incorporation of prior information if MCMC algorithms and posteriors are wel
Externí odkaz:
http://arxiv.org/abs/2402.15060
Two-sample hypothesis testing for large graphs is popular in cognitive science, probabilistic machine learning and artificial intelligence. While numerous methods have been proposed in the literature to address this problem, less attention has been d
Externí odkaz:
http://arxiv.org/abs/2402.11133
Much work in the parimutuel betting literature has discussed estimating event outcome probabilities or developing optimal wagering strategies, particularly for horse race betting. Some betting pools, however, involve betting not just on a single even
Externí odkaz:
http://arxiv.org/abs/2308.14339
Autor:
Barnett, Ian
Traditional methods for inference in change point detection often rely on a large number of observed data points and can be inaccurate in non-asymptotic settings. With the rise of mobile health and digital phenotyping studies, where patients are moni
Externí odkaz:
http://arxiv.org/abs/2304.04644
The COVID-19 pandemic has significantly impacted daily activity rhythms and life routines. Understanding the dynamics of these impacts on different groups of people is essential for creating environments where people's lives and well-being are least
Externí odkaz:
http://arxiv.org/abs/2303.04535
Autor:
Mandel, Francesca, Barnett, Ian
Neural networks are powerful predictive models, but they provide little insight into the nature of relationships between predictors and outcomes. Although numerous methods have been proposed to quantify the relative contributions of input features, s
Externí odkaz:
http://arxiv.org/abs/2301.11354
Regression models applied to network data where node attributes are the dependent variables poses a methodological challenge. As has been well studied, naive regression neither properly accounts for community structure, nor does it account for the de
Externí odkaz:
http://arxiv.org/abs/2301.04804