Publications (31)
Sample Efficient Bayesian Learning of Causal Graphs from Interventions
Zihan Zhou, Muhammad Qasim Elahi, Murat Kocaoglu
Causal discovery is a fundamental problem with applications spanning various areas in science and engineering. It is well understood that solely using observational data, one can o…
Sparse Quadratic Logistic Regression in Sub-quadratic Time
Karthikeyan Shanmugam, Murat Kocaoglu, Alexandros G. Dimakis +1
We consider support recovery in the quadratic logistic regression setting - where the target depends on both p linear terms and up to quadratic terms . Quadrat…
Partial Structure Discovery is Sufficient for No-regret Learning in Causal Bandits
Muhammad Qasim Elahi, Mahsa Ghasemi, Murat Kocaoglu
Causal knowledge about the relationships among decision variables and a reward variable in a bandit setting can accelerate the learning of an optimal decision. Current works often…
Entropic Causal Inference: Graph Identifiability
Spencer Compton, Kristjan Greenewald, Dmitriy Katz +1
Entropic causal inference is a recent framework for learning the causal graph between two variables from observational data by finding the information-theoretically simplest struct…
Information-Directed Sampling for Causal Bandits
Muhammad Qasim Elahi, Murat Kocaoglu, Mahsa Ghasemi
Causal bandits exploit structural relationships among variables to share information across interventions and accelerate the identification of high-reward decisions. In many applic…
Counterfactual Fairness by Combining Factual and Counterfactual Predictions
Zeyu Zhou, Tianci Liu, Ruqi Bai +3
In high-stake domains such as healthcare and hiring, the role of machine learning (ML) in decision-making raises significant fairness concerns. This work focuses on Counterfactual…