Zobrazeno 1 - 10
of 262
pro vyhledávání: '"Wiggins, Chris"'
Autor:
Li, Kathy, Urteaga, Iñigo, Shea, Amanda, Vitzthum, Virginia J., Wiggins, Chris H., Elhadad, Noémie
Mobile health (mHealth) apps such as menstrual trackers provide a rich source of self-tracked health observations that can be leveraged for health-relevant research. However, such data streams have questionable reliability since they hinge on user ad
Externí odkaz:
http://arxiv.org/abs/2102.12439
Autor:
Bliss, Nadya, Bradley, Elizabeth, Garland, Joshua, Menczer, Filippo, Ruston, Scott W., Starbird, Kate, Wiggins, Chris
In the 21st Century information environment, adversarial actors use disinformation to manipulate public opinion. The distribution of false, misleading, or inaccurate information with the intent to deceive is an existential threat to the United States
Externí odkaz:
http://arxiv.org/abs/2012.08572
Autor:
Li, Kathy, Urteaga, Iñigo, Wiggins, Chris H., Druet, Anna, Shea, Amanda, Vitzthum, Virginia J., Elhadad, Noémie
The menstrual cycle is a key indicator of overall health for women of reproductive age. Previously, menstruation was primarily studied through survey results; however, as menstrual tracking mobile apps become more widely adopted, they provide an incr
Externí odkaz:
http://arxiv.org/abs/1909.11211
Autor:
Tansey, Wesley, Li, Kathy, Zhang, Haoran, Linderman, Scott W., Rabadan, Raul, Blei, David M., Wiggins, Chris H.
Personalized cancer treatments based on the molecular profile of a patient's tumor are an emerging and exciting class of treatments in oncology. As genomic tumor profiling is becoming more common, targeted treatments to specific molecular alterations
Externí odkaz:
http://arxiv.org/abs/1812.05691
Autor:
Urteaga, Iñigo, Wiggins, Chris H.
We here adopt Bayesian nonparametric mixture models to extend multi-armed bandits in general, and Thompson sampling in particular, to scenarios where there is reward model uncertainty. In the stochastic multi-armed bandit, the reward for the played a
Externí odkaz:
http://arxiv.org/abs/1808.02932
Autor:
Urteaga, Iñigo, Wiggins, Chris H.
We extend Bayesian multi-armed bandit (MAB) algorithms beyond their original setting by making use of sequential Monte Carlo (SMC) methods. A MAB is a sequential decision making problem where the goal is to learn a policy that maximizes long term pay
Externí odkaz:
http://arxiv.org/abs/1808.02933
Autor:
Urteaga, Iñigo, Wiggins, Chris H.
Publikováno v:
Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR 84:698-706, 2018
In many biomedical, science, and engineering problems, one must sequentially decide which action to take next so as to maximize rewards. One general class of algorithms for optimizing interactions with the world, while simultaneously learning how the
Externí odkaz:
http://arxiv.org/abs/1709.03163
Autor:
Urteaga, Iñigo, Wiggins, Chris H.
Reinforcement learning studies how to balance exploration and exploitation in real-world systems, optimizing interactions with the world while simultaneously learning how the world operates. One general class of algorithms for such learning is the mu
Externí odkaz:
http://arxiv.org/abs/1709.03162