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Invited Paper Session

New Advances in Optimization Algorithms for Causal Discovery

Sun, Aug 3, 4:00 PM - 5:50 PM Room CC-104A Music City Center

Abhishek RoyOrganizerSoham JanaChair

Section on Statistical Computing co: IMSco: Section on Statistical Learning and Data Science

5 Presentations

Bridging causality and deep learning with causal generative models

4:05 PM - 4:25 PM

Bryon Aragam (The University of Chicago)

Greedy optimization Misspecified Nonparametric Model Selection Laplace approximation Nonparametric Graphical Models

Likelihood-based differentiable structure learning

4:25 PM - 4:45 PM

Pradeep Ravikumar (Carnegie Mellon University)

DAG Learning Identifiability Sparsest model Regularization

Enhancing Causal Effect Estimation with Diffusion-Generated Data

4:45 PM - 5:05 PM

Co-authors: Xiaotong Shen (University of Minnesota), Wei Pan (University of Minnesota)

Causal effect estimation Data augmentation Unmeasured confounding Generative models Transfer learning

Stochastic Optimization Algorithms for Instrumental Variable Regression with Streaming Data

5:05 PM - 5:25 PM

Abhishek Roy (Texas A&M University)

Online Instrumental Variable Regression Conditional Stochastic Optimization Stochastic approximation Causal Inference Streaming Data

Advancing Causal Structure Learning: Addressing Challenges with Latent Confounders

5:25 PM - 5:45 PM

Biwei Huang (Halicioğlu Data Science Institute (HDSI), UC San Diego (UCSD))

Casual Discovery Latent Confounders

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