12 citations · 25 across the 13 of their papers we have counts for
18 papers
Power Constrained Nonstationary Bandits with Habituation and Recovery Dynamics
Fengxu Li, Stephanie M. Carpenter, Matthew P. Buman +1
A common challenge for decision makers is selecting actions whose rewards are unknown and evolve over time based on prior policies. For instance, repeated use may reduce an action'…
Finite-Time Guarantees for Multi-Agent Combinatorial Bandits with Nonstationary Rewards
Katherine B. Adams, Justin J. Boutilier, Qinyang He +1
We study a sequential resource allocation problem where a decision maker selects subsets of agents at each period to maximize overall outcomes without prior knowledge of individual…
Non-stationary Bandits with Habituation and Recovery Dynamics and Knapsack Constraints
Qinyang He, Yonatan Mintz
Multi-armed bandit models have proven to be useful in modeling many real world problems in the areas of control and sequential decision making with partial information. However, in…
An Adaptive Optimization Approach to Personalized Financial Incentives in Mobile Behavioral Weight Loss Interventions
Qiaomei Li, Kara L. Gavin, Corrine I. Voils +1
Obesity is a critical healthcare issue affecting the United States. The least risky treatments available for obesity are behavioral interventions meant to promote diet and exercise…
Planning a Community Approach to Diabetes Care in Low- and Middle-Income Countries Using Optimization
Katherine B. Adams, Justin J. Boutilier, Sarang Deo +1
Diabetes is a global health priority, especially in low- and-middle-income countries, where over 50% of premature deaths are attributed to high blood glucose. Community Health Work…
Model Based Reinforcement Learning for Personalized Heparin Dosing
Qinyang He, Yonatan Mintz
A key challenge in sequential decision making is optimizing systems safely under partial information. While much of the literature has focused on the cases of either partially know…
Optimal Policy for Inventory Management with Periodic and Controlled Resets
Yoon Lee, Yonatan Mintz, Anil Aswani +2
Inventory management problems with periodic and controllable resets occur in the context of managing water storage in the developing world and retailing limited-time availability p…
The Game of Hidden Rules: A New Kind of Benchmark Challenge for Machine Learning
Eric Pulick, Shubham Bharti, Yiding Chen +4
As machine learning (ML) is more tightly woven into society, it is imperative that we better characterize ML's strengths and limitations if we are to employ it responsibly. Existin…
A Mixed-Integer Programming Approach to Training Dense Neural Networks
Vrishabh Patil, Yonatan Mintz
Artificial Neural Networks (ANNs) are prevalent machine learning models that are applied across various real-world classification tasks. However, training ANNs is time-consuming an…
Hard Choices in Artificial Intelligence
Roel Dobbe, Thomas Krendl Gilbert, Yonatan Mintz
As AI systems are integrated into high stakes social domains, researchers now examine how to design and operate them in a safe and ethical manner. However, the criteria for identif…
Optimal Local Explainer Aggregation for Interpretable Prediction
Qiaomei Li, Rachel Cummings, Yonatan Mintz
A key challenge for decision makers when incorporating black box machine learned models into practice is being able to understand the predictions provided by these models. One prop…
Hard Choices in Artificial Intelligence: Addressing Normative Uncertainty through Sociotechnical Commitments
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. However, the p…
Designing Real-Time Prices to Reduce Load Variability with HVAC
John Audie Cabrera, Yonatan Mintz, Jhoanna Rhodette Pedrasa +1
Utilities use demand response to shift or reduce electricity usage of flexible loads, to better match electricity demand to power generation. A common mechanism is peak pricing (PP…
Non-Stationary Bandits with Habituation and Recovery Dynamics
Yonatan Mintz, Anil Aswani, Philip Kaminsky +2
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 rewa…
Local Water Storage Control for the Developing World
Yonatan Mintz, Zuo-Jun Max Shen, Anil Aswani
Most cities in India do not have water distribution networks that provide water throughout the entire day. As a result, it is common for homes and apartment buildings to utilize wa…
Behavioral Analytics for Myopic Agents
Yonatan Mintz, Anil Aswani, Philip Kaminsky +2
Many multi-agent systems have the structure of a single coordinator providing behavioral or financial incentives to a large number of agents. Two challenges faced by the coordinato…
Control Synthesis for Bilevel Linear Model Predictive Control
Yonatan Mintz, John Audie Cabrera, Jhoanna Rhodette Pedrasa +1
Distributed model predictive control (MPC) is either cooperative or competitive, and control-theoretic properties have been less studied in the competitive (e.g., game theory) sett…
Polynomial-Time Approximation for Nonconvex Optimization Problems with an L1-Constraint
Yonatan Mintz, Anil Aswani
Nonconvex optimization problems with an L1-constraint are ubiquitous, and are found in many application domains including: optimal control of hybrid systems, machine learning and s…