15 citations · 28 across the 10 of their papers we have counts for
10 papers
Improved Policy Evaluation for Randomized Trials of Algorithmic Resource Allocation
Aditya Mate, Bryan Wilder, Aparna Taneja +1
We consider the task of evaluating policies of algorithmic resource allocation through randomized controlled trials (RCTs). Such policies are tasked with optimizing the utilization…
Decision-Focused Evaluation: Analyzing Performance of Deployed Restless Multi-Arm Bandits
Paritosh Verma, Shresth Verma, Aditya Mate +2
Restless multi-arm bandits (RMABs) is a popular decision-theoretic framework that has been used to model real-world sequential decision making problems in public health, wildlife c…
Scalable Decision-Focused Learning in Restless Multi-Armed Bandits with Application to Maternal and Child Health
Kai Wang, Shresth Verma, Aditya Mate +5
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…
Field Study in Deploying Restless Multi-Armed Bandits: Assisting Non-Profits in Improving Maternal and Child Health
Aditya Mate, Lovish Madaan, Aparna Taneja +6
The widespread availability of cell phones has enabled non-profits to deliver critical health information to their beneficiaries in a timely manner. This paper describes our work t…
Solving Structured Hierarchical Games Using Differential Backward Induction
Zun Li, Feiran Jia, Aditya Mate +4
From large-scale organizations to decentralized political systems, hierarchical strategic decision making is commonplace. We introduce a novel class of structured hierarchical game…
Selective Intervention Planning using Restless Multi-Armed Bandits to Improve Maternal and Child Health Outcomes
Siddharth Nishtala, Lovish Madaan, Aditya Mate +11
India has a maternal mortality ratio of 113 and child mortality ratio of 2830 per 100,000 live births. Lack of access to preventive care information is a major contributing factor…
Efficient Algorithms for Finite Horizon and Streaming Restless Multi-Armed Bandit Problems
Aditya Mate, Arpita Biswas, Christoph Siebenbrunner +2
We propose Streaming Bandits, a Restless Multi Armed Bandit (RMAB) framework in which heterogeneous arms may arrive and leave the system after staying on for a finite lifetime. Str…
A Game-Theoretic Approach for Hierarchical Epidemic Control
Feiran Jia, Aditya Mate, Zun Li +5
We design and analyze a multi-level game-theoretic model of hierarchical policy interventions for epidemic control, such as those in response to the COVID-19 pandemic. Our model ca…
Collapsing Bandits and Their Application to Public Health Interventions
Aditya Mate, Jackson A. Killian, Haifeng Xu +2
We propose and study Collpasing Bandits, a new restless multi-armed bandit (RMAB) setting in which each arm follows a binary-state Markovian process with a special structure: when…
End-to-End Game-Focused Learning of Adversary Behavior in Security Games
Andrew Perrault, Bryan Wilder, Eric Ewing +3
Stackelberg security games are a critical tool for maximizing the utility of limited defense resources to protect important targets from an intelligent adversary. Motivated by gree…