103 citations · 104 across the 5 of their papers we have counts for
5 papers
Relational Causal Discovery with Latent Confounders
Matteo Negro, Andrea Piras, Ragib Ahsan +2
Estimating causal effects from real-world relational data can be challenging when the underlying causal model and potential confounders are unknown. While several causal discovery…
Learning Relational Causal Models with Cycles through Relational Acyclification
Ragib Ahsan, David Arbour, Elena Zheleva
In real-world phenomena which involve mutual influence or causal effects between interconnected units, equilibrium states are typically represented with cycles in graphical models.…
Non-Parametric Inference of Relational Dependence
Ragib Ahsan, Zahra Fatemi, David Arbour +1
Independence testing plays a central role in statistical and causal inference from observational data. Standard independence tests assume that the data samples are independent and…
Relational Causal Models with Cycles:Representation and Reasoning
Ragib Ahsan, David Arbour, Elena Zheleva
Causal reasoning in relational domains is fundamental to studying real-world social phenomena in which individual units can influence each other's traits and behavior. Dynamics bet…
Correcting for Selection Bias in Learning-to-rank Systems
Zohreh Ovaisi, Ragib Ahsan, Yifan Zhang +2
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. However, these dat…