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In a sequential multiple-assignment randomized trial (SMART), a sequence of treatments is given to a patient over multiple stages. In each stage, randomization may be done to allocate patients to different treatment groups. Even though…

Methodology · Statistics 2024-01-09 Rik Ghosh , Bibhas Chakraborty , Inbal Nahum-Shani , Megan E. Patrick , Palash Ghosh

Real-world recommender systems often need to balance multiple objectives when deciding which recommendations to present to users. These include behavioural signals (e.g. clicks, shares, dwell time), as well as broader objectives (e.g.…

Information Retrieval · Computer Science 2024-09-17 Olivier Jeunen , Jatin Mandav , Ivan Potapov , Nakul Agarwal , Sourabh Vaid , Wenzhe Shi , Aleksei Ustimenko

A multi-arm multi-stage trial is a multi-arm trial which includes interim analyses - analysing the data at certain specified points, generally discontinuing treatments which are concluded to not work and proceeding with the remainder. It is…

Methodology · Statistics 2022-11-14 Martin Law

We characterize the optimal reward functions (scoring rules) that incentivize an agent to acquire information and report it truthfully to the principal. The optimal scoring rules let the agent make a simple binary bet in single-dimensional…

Computer Science and Game Theory · Computer Science 2025-10-03 Jason D. Hartline , Yingkai Li , Liren Shan , Yifan Wu

Due to accelerating urbanization, the importance of solving the signal control problem increases. This paper analyzes various existing methods and suggests options for increasing the number of agents to reduce the average travel time.…

Artificial Intelligence · Computer Science 2024-06-21 Maksim Tislenko , Dmitrii Kisilev

Conventional treatment policies map patient covariates to a single recommended intervention in order to maximize expected clinical outcomes. Although a rich body of causal inference methods has been developed to estimate such policies,…

Machine Learning · Computer Science 2026-05-20 Laura Fuentes-Vicente , Mathieu Even , Gaëlle Dormion , Antoine Chambaz , Uri Shalit , Julie Josse

This paper introduces a novel causal framework for multi-stage decision-making in natural language action spaces where outcomes are only observed after a sequence of actions. While recent approaches like Proximal Policy Optimization (PPO)…

Computation and Language · Computer Science 2025-02-26 Bohan Zhang , Yixin Wang , Paramveer S. Dhillon

In this effort, we consider the impact of regularization on the diversity of actions taken by policies generated from reinforcement learning agents trained using a policy gradient. Policy gradient agents are prone to entropy collapse, which…

Machine Learning · Computer Science 2023-10-10 Andrew Starnes , Anton Dereventsov , Clayton Webster

The methodological issues and statistical complexities of analyzing university students with migrant backgrounds is explored, focusing on Italian data from the University of Milano-Bicocca. With the increasing size of migrant populations…

Applications · Statistics 2025-01-13 Lorenzo Giammei , Laura Terzera , Fulvia Mecatti

Often, vaccination programs are carried out based on self-interest rather than being mandatory. Owing to the perceptions about risks associated with vaccines and the `herd immunity' effect, it may provide suboptimal vaccination coverage for…

Physics and Society · Physics 2012-07-20 Hai-Feng Zhang , Zhi-Xi Wu , Xiao-Ke Xu , Michael Small , Bing-Hong Wang

Two-stage randomization is a powerful design for estimating treatment effects in the presence of interference; that is, when one individual's treatment assignment affects another individual's outcomes. Our motivating example is a two-stage…

Applications · Statistics 2017-05-02 Guillaume Basse , Avi Feller

We study variants of the Optimal Refugee Resettlement problem where a set $F$ of refugee families need to be allocated to a set $L$ of possible places of resettlement in a feasible and optimal way. Feasibility issues emerge from the…

Computer Science and Game Theory · Computer Science 2024-08-19 Jiehua Chen , Ildikó Schlotter , Sofia Simola

I examine the problem of treatment choice when a planner observes (i) covariates that describe each member of a population of interest and (ii) the outcomes of an experiment in which subjects randomly drawn from this population are randomly…

Applications · Statistics 2013-02-01 Charles F. Manski

We study the problem of selecting the top-k candidates from a pool of applicants, where each candidate is associated with a score indicating his/her aptitude. Depending on the specific scenario, such as job search or college admissions,…

Computers and Society · Computer Science 2021-03-08 Giorgio Barnabo' , Carlos Castillo , Michael Mathioudakis , Sergio Celis

This article discusses the application of stochastic intervention to find the optimal treatment distribution yielding a high value of expected potential outcome under the setting where the number of treatments is allowed to vary with $n$.…

Statistics Theory · Mathematics 2026-04-22 Rohit Chaudhuri

Network-based intervention strategies can be effective and cost-efficient approaches to curtailing harmful contagions in myriad settings. As studied, these strategies are often impractical to implement, as they typically assume complete…

Physics and Society · Physics 2020-09-09 Samuel F. Rosenblatt , Jeffrey A. Smith , G. Robin Gauthier , Laurent Hébert-Dufresne

Given two possible treatments, there may exist subgroups who benefit greater from one treatment than the other. This problem is relevant to the field of marketing, where treatments may correspond to different ways of selling a product. It…

Machine Learning · Statistics 2016-05-16 Derek Feng , Xiaofei Wang

The United States has introduced a special humanitarian parole process for Ukrainian citizens in response to Russia 2022 invasion of Ukraine. To qualify for parole, Ukrainian applicants must have a sponsor in the United States. In…

Physics and Society · Physics 2023-10-11 Fatemeh Farajzadeh , Ryan B. Killea , Alexander Teytelboym , Andrew C. Trapp

This paper examines the short- and long-term effects of immigrant assimilation policies in Brazil after the Mass Migration period. It focuses on the Nationalization Campaign, launched amid rising anti-immigrant sentiment during the Great…

General Economics · Economics 2025-10-22 Vinicius Schuabb

Optimal treatment regimes are personalized policies for making a treatment decision based on subject characteristics, with the policy chosen to maximize some value. It is common to aim to maximize the mean outcome in the population, via a…

Methodology · Statistics 2022-02-28 Liu Leqi , Edward H. Kennedy
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