activity
20192026
most citedCollecting, Classifying, Analyzing, and Using Real-World Elections

3 citations · 24 across the 52 of their papers we have counts for

collaborators
Showing 2024Show all

11 papers · 1 filter

cs.AI2024★ 2 cited

Towards Foundation-model-based Multiagent System to Accelerate AI for Social Impact

Yunfan Zhao, Niclas Boehmer, Aparna Taneja +1

AI for social impact (AI4SI) offers significant potential for addressing complex societal challenges in areas such as public health, agriculture, education, conservation, and publi…

cs.AI2024★ 1 cited

Optimizing Vital Sign Monitoring in Resource-Constrained Maternal Care: An RL-Based Restless Bandit Approach

Niclas Boehmer, Yunfan Zhao, Guojun Xiong +5

Maternal mortality remains a significant global public health challenge. One promising approach to reducing maternal deaths occurring during facility-based childbirth is through ea…

cs.GT2024

Multiwinner Temporal Voting with Aversion to Change

Valentin Zech, Niclas Boehmer, Edith Elkind +1

We study two-stage committee elections where voters have dynamic preferences over candidates; at each stage, a committee is chosen under a given voting rule. We are interested in i…

cs.GT2024

Worst- and Average-Case Robustness of Stable Matchings: (Counting) Complexity and Experiments

Kimon Boehmer, Niclas Boehmer

Focusing on the bipartite Stable Marriage problem, we investigate different robustness measures related to stable matchings. We analyze the computational complexity of computing th…

cs.LG2024

Balancing Act: Prioritization Strategies for LLM-Designed Restless Bandit Rewards

Shresth Verma, Niclas Boehmer, Lingkai Kong +1

LLMs are increasingly used to design reward functions based on human preferences in Reinforcement Learning (RL). We focus on LLM-designed rewards for Restless Multi-Armed Bandits,…

cs.GT2024

Escape Sensing Games: Detection-vs-Evasion in Security Applications

Niclas Boehmer, Minbiao Han, Haifeng Xu +1

Traditional game-theoretic research for security applications primarily focuses on the allocation of external protection resources to defend targets. This work puts forward the stu…

cs.HC2024★ 1 cited

Preliminary Study of the Impact of AI-Based Interventions on Health and Behavioral Outcomes in Maternal Health Programs

Arpan Dasgupta, Niclas Boehmer, Neha Madhiwalla +4

Automated voice calls are an effective method of delivering maternal and child health information to mothers in underserved communities. One method to fight dwindling listenership…

cs.LG2024

Evaluating the Effectiveness of Index-Based Treatment Allocation

Niclas Boehmer, Yash Nair, Sanket Shah +3

When resources are scarce, an allocation policy is needed to decide who receives a resource. This problem occurs, for instance, when allocating scarce medical resources and is ofte…

cs.GT2024

Guide to Numerical Experiments on Elections in Computational Social Choice

Niclas Boehmer, Piotr Faliszewski, Łukasz Janeczko +7

We analyze how numerical experiments regarding elections were conducted within the computational social choice literature (focusing on papers published in the IJCAI, AAAI, and AAMA…

cs.CY2024★ 2 cited

Enabling the Digital Democratic Revival: A Research Program for Digital Democracy

Davide Grossi, Ulrike Hahn, Michael Mäs +26

This white paper outlines a long-term scientific vision for the development of digital-democracy technology. We contend that if digital democracy is to meet the ambition of enablin…

stat.ME2024

Properties of the Mallows Model Depending on the Number of Alternatives: A Warning for an Experimentalist

Niclas Boehmer, Piotr Faliszewski, Sonja Kraiczy

The Mallows model is a popular distribution for ranked data. We empirically and theoretically analyze how the properties of rankings sampled from the Mallows model change when incr…