16 citations · 42 across the 22 of their papers we have counts for
6 papers · 1 filter
Domain Generalization -- A Causal Perspective
Paras Sheth, Raha Moraffah, K. Selçuk Candan +2
Machine learning models rely on various assumptions to attain high accuracy. One of the preliminary assumptions of these models is the independent and identical distribution, which…
Improving Vaccine Stance Detection by Combining Online and Offline Data
Anique Tahir, Lu Cheng, Paras Sheth +1
Differing opinions about COVID-19 have led to various online discourses regarding vaccines. Due to the detrimental effects and the scale of the COVID-19 pandemic, detecting vaccine…
Estimating Topic Exposure for Under-Represented Users on Social Media
Mansooreh Karami, Ahmadreza Mosallanezhad, Paras Sheth +1
Online Social Networks (OSNs) facilitate access to a variety of data allowing researchers to analyze users' behavior and develop user behavioral analysis models. These models rely…
CoVaxNet: An Online-Offline Data Repository for COVID-19 Vaccine Hesitancy Research
Bohan Jiang, Paras Sheth, Baoxin Li +1
Despite the astonishing success of COVID-19 vaccines against the virus, a substantial proportion of the population is still hesitant to be vaccinated, undermining governmental effo…
Causal Disentanglement with Network Information for Debiased Recommendations
Paras Sheth, Ruocheng Guo, Lu Cheng +2
Recommender systems aim to recommend new items to users by learning user and item representations. In practice, these representations are highly entangled as they consist of inform…
Evaluation Methods and Measures for Causal Learning Algorithms
Lu Cheng, Ruocheng Guo, Raha Moraffah +3
The convenient access to copious multi-faceted data has encouraged machine learning researchers to reconsider correlation-based learning and embrace the opportunity of causality-ba…