TP3b.3

Non-negative DAG Learning from Streaming Data

Madeline Navarro, Rice University, United States; Samuel Rey, Universidad Rey Juan Carlos, Spain; Gonzalo Mateos, University of Rochester, United States; Santiago Segarra, Rice University, United States
Session:
TP3b: Causality in Graph Learning Lecture
Track:
Networks and Graphs
Location:
Room 3
Presentation Time:
Tue, 27 Oct, 16:20 - 16:45 PT (UTC -7)
Session Chair:
Samuel Rey Escudero, Universidad Rey Juan Carlos, Spain
Presentation
Discussion
Resources
No resources available.
Session TP3b
TP3b.1: Causal Discovery in Equal Variance Linear Gaussian DAGs via SURE-Tuned Ridge Regression
Sambit Mishra, Urbashi Mitra, University of Southern California, United States
TP3b.2: Epidemiological Causal Graph Identification: Challenges, Identifiability and Algorithms
Sambit Mishra, University of Southern California, United States; Yingying Wang, Christine K. Johnson, University of California, Davis, United States; Urbashi Mitra, University of Southern California, United States
TP3b.3: Non-negative DAG Learning from Streaming Data
Madeline Navarro, Rice University, United States; Samuel Rey, Universidad Rey Juan Carlos, Spain; Gonzalo Mateos, University of Rochester, United States; Santiago Segarra, Rice University, United States
TP3b.4: Optimal Interventions for Sequential Causal Discovery
Guanchao Feng, Stony Brook University, United States; Kurt Butler, The University of Edinburgh, United Kingdom; Shervin Jarrahi, Petar M. Djuric, Stony Brook University, United States
TP3b.5: Causal Discovery in Nonlinear Time Series with Sparse Structural Shocks
Panagiotis Misiakos, Markus Püschel, ETH Zurich, Switzerland
Contacts