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Harnessing the wide‐spread availability of cell phones, many nonprofits have launched mobile health (mHealth) programs to deliver information via voice or text to beneficiaries in underserved communities, with maternal and infant health being a ...

Restless multi-arm bandits (RMABs), a class of resource allocation problems with broad application in areas such as healthcare, online advertising, and anti-poaching, have recently been studied from a multi-agent reinforcement learning perspective. Prior ...

The declining participation of beneficiaries over time is a key concern in public health programs. A popular strategy for improving retention is to have health workers 'intervene' on beneficiaries at risk of dropping out. However, the availability and ...

Maternal and child health is a global priority, reflected in the UN Sustainable Development Goal 3.1. Mobile health (mHealth) programs, using automated voice messages, are a vital tool for NGOs to disseminate health information in underserved ...

Underserved communities face critical health challenges due to lack of access to timely and reliable information. Nongovernmental organizations are leveraging the widespread use of cellphones to combat these healthcare challenges and spread ...

Optimization tasks situated in incomplete information settings are often preceded by a prediction problem to estimate the missing information; past work shows the traditional predict-then-optimize (PTO) framework can be improved by training a ...

The success of many healthcare programs depends on participants' adherence. We consider the problem of scheduling interventions in low resource settings (e.g., placing timely support calls from health workers) to increase adherence and/or engagement. Past ...

This workshop will bring together researchers and practitioners across different strands of data science research and a wide range of important real-world application domains. The objective is to share the current state of research and practice, explore ...

We consider the task of evaluating policies of algorithmic resource allocation through randomized controlled trials (RCTs). Such policies are tasked with optimizing the utilization of limited intervention resources, with the goal of maximizing the ...

Predict-then-optimize is a common paradigm for optimization tasks situated in incomplete informational settings, in which an agent estimates missing parameters and then optimizes over these predicted parameters. One proposed improvement to this predict-...

Mobile Health Awareness programs in underserved communities often suffer from diminishing engagement over time and health workers have to make live service calls to encourage beneficiaries' participation. Owing to health workers' limited availability, we ...

Restless multi-armed bandits (RMABs) extend multi-armed bandits to allow for stateful arms, where the state of each arm evolves restlessly with different transitions depending on whether that arm is pulled. Solving RMABs requires information on transition ...

Underserved communities face critical health challenges due to lack of access to timely and reliable information. Nongovernmental organizations are leveraging the widespread use of cellphones to combat these healthcare challenges and spread preventative ...

In 2020, maternal mortality in India was estimated to be as high as 130 deaths per 100K live births, nearly twice the UN's target. To improve health outcomes, the non-profit ARMMAN sends automated voice messages to expecting and new mothers across India. ...

This paper studies restless multi-armed bandit (RMAB) problems with unknown arm transition dynamics but with known correlated arm features. The goal is to learn a model to predict transition dynamics given features, where the Whittle index policy solves ...

Restless multi-armed bandits (RMABs) are an important model to optimize allocation of limited resources in sequential decision-making settings. Typical RMABs assume the budget — the number of arms pulled — to be fixed for each step in the planning ...

We propose a method to detect changes in the geometry of a city using panoramic images captured by a car driving around the city. The proposed method can be used to significantly optimize the process of updating the 3D model of an urban environment that ...

In this paper, we propose a method to detect changes in the geometry of a city using panoramic images captured by a car driving around the city. We designed our approach to account for all the challenges involved in a large scale application of change ...

The availability of geolocated panoramic images of urban environments has been increasing in the recent past thanks to services like Google Street View, Microsoft Street Side, and Navteq. Despite the fact that their primary application is in street ...

Capturing the motion of two hands interacting with an object is a very challenging task due to the large number of degrees of freedom, self-occlusions, and similarity between the fingers, even in the case of multiple cameras observing the scene. In this ...