33 citations · 49 across the 10 of their papers we have counts for
10 papers
RoCourseNet: Distributionally Robust Training of a Prediction Aware Recourse Model
Hangzhi Guo, Feiran Jia, Jinghui Chen +2
Counterfactual (CF) explanations for machine learning (ML) models are preferred by end-users, as they explain the predictions of ML models by providing a recourse (or contrastive)…
CounterNet: End-to-End Training of Prediction Aware Counterfactual Explanations
Hangzhi Guo, Thanh Hong Nguyen, Amulya Yadav
This work presents CounterNet, a novel end-to-end learning framework which integrates Machine Learning (ML) model training and the generation of corresponding counterfactual (CF) e…
Clinical trial of an AI-augmented intervention for HIV prevention in youth experiencing homelessness
Bryan Wilder, Laura Onasch-Vera, Graham Diguiseppi +5
Youth experiencing homelessness (YEH) are subject to substantially greater risk of HIV infection, compounded both by their lack of access to stable housing and the disproportionate…
Preliminary Results from a Peer-Led, Social Network Intervention, Augmented by Artificial Intelligence to Prevent HIV among Youth Experiencing Homelessness
Eric Rice, Laura Onasch-Vera, Graham T. DiGuiseppi +5
Each year, there are nearly 4 million youth experiencing homelessness (YEH) in the United States with HIV prevalence ranging from 3 to 11.5%. Peer change agent (PCA) models for HIV…
Exploring Algorithmic Fairness in Robust Graph Covering Problems
Aida Rahmattalabi, Phebe Vayanos, Anthony Fulginiti +4
Fueled by algorithmic advances, AI algorithms are increasingly being deployed in settings subject to unanticipated challenges with complex social effects. Motivated by real-world d…
Influence Maximization for Social Good: Use of Social Networks in Low Resource Communities
Amulya Yadav
This thesis proposal makes the following technical contributions: (i) we provide a definition of the Dynamic Influence Maximization Under Uncertainty (or DIME) problem, which model…
Artificial Intelligence for Low-Resource Communities: Influence Maximization in an Uncertain World
Amulya Yadav
The potential of Artificial Intelligence (AI) to tackle challenging problems that afflict society is enormous, particularly in the areas of healthcare, conservation and public safe…
Activating the "Breakfast Club": Modeling Influence Spread in Natural-World Social Networks
Lily Hu, Bryan Wilder, Amulya Yadav +2
While reigning models of diffusion have privileged the structure of a given social network as the key to informational exchange, real human interactions do not appear to take place…
Pilot Testing an Artificial Intelligence Algorithm That Selects Homeless Youth Peer Leaders Who Promote HIV Testing
Eric Rice, Robin Petering, Jaih Craddock +3
Objective. To pilot test an artificial intelligence (AI) algorithm that selects peer change agents (PCA) to disseminate HIV testing messaging in a population of homeless youth. Met…
Using Social Networks to Aid Homeless Shelters: Dynamic Influence Maximization under Uncertainty - An Extended Version
Amulya Yadav, Hau Chan, Albert Jiang +3
This paper presents HEALER, a software agent that recommends sequential intervention plans for use by homeless shelters, who organize these interventions to raise awareness about H…