Search Results for author: Aditya Mate

Found 10 papers, 1 papers with code

A resource-constrained stochastic scheduling algorithm for homeless street outreach and gleaning edible food

no code implementations15 Mar 2024 Conor M. Artman, Aditya Mate, Ezinne Nwankwo, Aliza Heching, Tsuyoshi Idé, Jiří\, Navrátil, Karthikeyan Shanmugam, Wei Sun, Kush R. Varshney, Lauri Goldkind, Gidi Kroch, Jaclyn Sawyer, Ian Watson

We developed a common algorithmic solution addressing the problem of resource-constrained outreach encountered by social change organizations with different missions and operations: Breaking Ground -- an organization that helps individuals experiencing homelessness in New York transition to permanent housing and Leket -- the national food bank of Israel that rescues food from farms and elsewhere to feed the hungry.

Scheduling Thompson Sampling

Improved Policy Evaluation for Randomized Trials of Algorithmic Resource Allocation

no code implementations6 Feb 2023 Aditya Mate, Bryan Wilder, Aparna Taneja, Milind Tambe

We consider the task of evaluating policies of algorithmic resource allocation through randomized controlled trials (RCTs).

counterfactual

Decision-Focused Evaluation: Analyzing Performance of Deployed Restless Multi-Arm Bandits

no code implementations19 Jan 2023 Paritosh Verma, Shresth Verma, Aditya Mate, Aparna Taneja, Milind Tambe

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 conservation, communication systems, and beyond.

Decision Making

Scalable Decision-Focused Learning in Restless Multi-Armed Bandits with Application to Maternal and Child Health

no code implementations2 Feb 2022 Kai Wang, Shresth Verma, Aditya Mate, Sanket Shah, Aparna Taneja, Neha Madhiwalla, Aparna Hegde, Milind Tambe

To address this shortcoming, we propose a novel approach for decision-focused learning in RMAB that directly trains the predictive model to maximize the Whittle index solution quality.

Multi-Armed Bandits Scheduling

Efficient Algorithms for Finite Horizon and Streaming Restless Multi-Armed Bandit Problems

no code implementations8 Mar 2021 Aditya Mate, Arpita Biswas, Christoph Siebenbrunner, Susobhan Ghosh, Milind Tambe

Our contributions are as follows: (1) We derive conditions under which our problem satisfies indexability, a precondition that guarantees the existence and asymptotic optimality of the Whittle Index solution for RMABs.

Multi-Armed Bandits

Collapsing Bandits and Their Application to Public Health Intervention

1 code implementation NeurIPS 2020 Aditya Mate, Jackson Killian, Haifeng Xu, Andrew Perrault, Milind Tambe

Our main contributions are as follows: (i) Building on the Whittle index technique for RMABs, we derive conditions under which the Collapsing Bandits problem is indexable.

Collapsing Bandits and Their Application to Public Health Interventions

no code implementations5 Jul 2020 Aditya Mate, Jackson A. Killian, Haifeng Xu, Andrew Perrault, Milind Tambe

(ii) We exploit the optimality of threshold policies to build fast algorithms for computing the Whittle index, including a closed-form.

End-to-End Game-Focused Learning of Adversary Behavior in Security Games

no code implementations3 Mar 2019 Andrew Perrault, Bryan Wilder, Eric Ewing, Aditya Mate, Bistra Dilkina, Milind Tambe

Stackelberg security games are a critical tool for maximizing the utility of limited defense resources to protect important targets from an intelligent adversary.

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