no code implementations • 29 Feb 2024 • Vrishabh Patil, Kara Hoppe, Yonatan Mintz
A key challenge in medical decision making is learning treatment policies for patients with limited observational data.
no code implementations • 1 Jul 2023 • Qiaomei Li, Kara L. Gavin, Corrine I. Voils, Yonatan Mintz
In this paper, we consider this challenge of designing personalized weight loss interventions that use direct financial incentives to motivate weight loss while remaining within a budget.
no code implementations • 30 Jun 2023 • Eric Pulick, Vladimir Menkov, Yonatan Mintz, Paul Kantor, Vicki Bier
Reliable real-world deployment of reinforcement learning (RL) methods requires a nuanced understanding of their strengths and weaknesses and how they compare to those of humans.
no code implementations • 10 May 2023 • Katherine B. Adams, Justin J. Boutilier, Sarang Deo, Yonatan Mintz
Yet, scalable models to design and implement CHW programs while accounting for screening, management, and patient enrollment decisions have not been proposed.
no code implementations • 19 Apr 2023 • Qinyang He, Yonatan Mintz
In this paper we propose such a framework to address the challenge of optimizing personalized heparin doses.
no code implementations • 20 Jul 2022 • Eric Pulick, Shubham Bharti, Yiding Chen, Vladimir Menkov, Yonatan Mintz, Paul Kantor, Vicki M. Bier
Existing benchmark environments for ML, such as board and video games, offer well-defined benchmarks for progress, but constituent tasks are often complex, and it is frequently unclear how task characteristics contribute to overall difficulty for the machine learner.
no code implementations • 3 Jan 2022 • Vrishabh Patil, Yonatan Mintz
Artificial Neural Networks (ANNs) are prevalent machine learning models that are applied across various real-world classification tasks.
no code implementations • 10 Jun 2021 • Roel Dobbe, Thomas Krendl Gilbert, Yonatan Mintz
In this paper, we examine the vagueness in debates about the safety and ethical behavior of AI systems.
no code implementations • 20 Mar 2020 • Qiaomei Li, Rachel Cummings, Yonatan Mintz
In contrast to other heuristic methods, we use an integer optimization framework to combine local explainers into a near-global aggregate explainer.
no code implementations • 20 Nov 2019 • Roel Dobbe, Thomas Krendl Gilbert, Yonatan Mintz
As AI systems become prevalent in high stakes domains such as surveillance and healthcare, researchers now examine how to design and implement them in a safe manner.
no code implementations • 26 Jul 2017 • Yonatan Mintz, Anil Aswani, Philip Kaminsky, Elena Flowers, Yoshimi Fukuoka
Many settings involve sequential decision-making where a set of actions can be chosen at each time step, each action provides a stochastic reward, and the distribution for the reward of each action is initially unknown.