no code implementations • 19 Feb 2024 • Rochana Chaturvedi, Sugat Chaturvedi, Elena Zheleva
We then use a meta-learning framework to examine heterogeneous treatment effects of intergroup interactions on an individual's group conformity in the light of communal, political, and socio-economic events.
no code implementations • 16 Oct 2023 • Ahmed Sayeed Faruk, Elena Zheleva
However, current approaches ignore potential spillover between interacting users, where the action of one user can impact the actions and rewards of other users.
no code implementations • 15 Jun 2023 • Zahra Fatemi, Minh Huynh, Elena Zheleva, Zamir Syed, Xiaojun Di
Our experiments demonstrate that the CDF-cold framework outperforms state-of-the-art forecasting models in predicting future values of multivariate time series data.
no code implementations • 4 Jun 2023 • Zahra Fatemi, Elena Zheleva
Contagion effect refers to the causal effect of peers' behavior on the outcome of an individual in social networks.
no code implementations • 27 May 2023 • Shishir Adhikari, Elena Zheleva
Heterogeneous peer influence (HPI) occurs when a unit's outcome is influenced differently by different peers based on their attributes and relationships, or when each unit has a different susceptibility to peer influence.
no code implementations • 16 Jan 2023 • Christopher Tran, Keith Burghardt, Kristina Lerman, Elena Zheleva
In this work, we provide a survey of state-of-the-art data-driven methods for heterogeneous treatment effect estimation using machine learning, broadly categorizing them as methods that focus on counterfactual prediction and methods that directly estimate the causal effect.
1 code implementation • 25 Aug 2022 • Ragib Ahsan, David Arbour, Elena Zheleva
We introduce relational acyclification, an operation specifically designed for relational models that enables reasoning about the identifiability of cyclic relational causal models.
1 code implementation • 30 Jun 2022 • Ragib Ahsan, Zahra Fatemi, David Arbour, Elena Zheleva
Independence testing plays a central role in statistical and causal inference from observational data.
1 code implementation • 25 Jun 2022 • Christopher Tran, Elena Zheleva
To address this problem, we develop a feature selection method that considers each feature's value for HTE estimation and learns the relevant parts of the causal structure from data.
no code implementations • 22 Feb 2022 • Ragib Ahsan, David Arbour, Elena Zheleva
To facilitate cycles in relational representation and learning, we introduce relational $\sigma$-separation, a new criterion for understanding relational systems with feedback loops.
1 code implementation • 27 Jan 2022 • Christopher Tran, Elena Zheleva
The Linear Threshold Model is a widely used model that describes how information diffuses through a social network.
1 code implementation • 12 Jan 2022 • Zohreh Ovaisi, Shelby Heinecke, Jia Li, Yongfeng Zhang, Elena Zheleva, Caiming Xiong
Robust machine learning is an increasingly important topic that focuses on developing models resilient to various forms of imperfect data.
no code implementations • 27 Oct 2021 • Yuzi He, Christopher Tran, Julie Jiang, Keith Burghardt, Emilio Ferrara, Elena Zheleva, Kristina Lerman
The popularity of online gaming has grown dramatically, driven in part by streaming and the billion-dollar e-sports industry.
1 code implementation • 4 Jun 2021 • Shishir Adhikari, Akshay Uppal, Robin Mermelstein, Tanya Berger-Wolf, Elena Zheleva
Cannabis legalization has been welcomed by many U. S. states but its role in escalation from tobacco e-cigarette use to cannabis vaping is unclear.
no code implementations • WS 2020 • Usman Shahid, Barbara Di Eugenio, Andrew Rojecki, Elena Zheleva
We describe work in progress on detecting and understanding the moral biases of news sources by combining framing theory with natural language processing.
no code implementations • 15 Apr 2020 • Zahra Fatemi, Elena Zheleva
Here, we show that cluster randomization does not ensure sufficient node randomization and it can lead to selection bias in which treatment and control nodes represent different populations of users.
2 code implementations • 1 Feb 2020 • Chainarong Amornbunchornvej, Elena Zheleva, Tanya Berger-Wolf
We demonstrate our approaches on an application for studying coordinated collective behavior and other real-world casual-inference datasets and show that our proposed approaches perform better than several existing methods in both simulated and real-world datasets.
no code implementations • 29 Jan 2020 • Zohreh Ovaisi, Ragib Ahsan, Yifan Zhang, Kathryn Vasilaky, Elena Zheleva
Click data collected by modern recommendation systems are an important source of observational data that can be utilized to train learning-to-rank (LTR) systems.
2 code implementations • 18 Dec 2019 • Chainarong Amornbunchornvej, Elena Zheleva, Tanya Y. Berger-Wolf
Typical operationalizations of Granger causality make a strong assumption that every time point of the effect time series is influenced by a combination of other time series with a fixed time delay.
1 code implementation • 31 Jan 2019 • Christopher Tran, Elena Zheleva
The causal effect of a treatment can vary from person to person based on their individual characteristics and predispositions.