Important Dates

Call For Papers






UAI 2016

Workshop Proceedings

The proceedings have been published through the CEUR Workshop Proceedings and are now available at this link. We also provide a BiBTeX file for convenience.

Draft Papers and Abstracts

The papers and abstracts below are drafts aimed to provide interested readers with additional detail on the presentations at the workshop. The proceedings of this workshop are separate (see above).

Causal Discovery with Latent Variables: the Measurement Problem (invited talk)

Richard Scheines


Discovering Dynamical Kinds (invited talk)

Benjamin Jantzen


Score-based vs Constraint-based Causal Learning in the Presence of Confounders

Sofia Triantafillou and Ioannis Tsamardinos

[Abstract] [PDF]

Causal Inference by Minimizing the Dual Norm of Bias: Kernel Matching & Weighting Estimators for Causal Effects

Nathan Kallus

[Abstract] [PDF]

Separating Sparse Signals from Correlated Noise in Binary Classification

Stephan Mandt, Florian Wenzel, Shinichi Nakajima, Christoph Lippert and Marius Kloft

[Abstract] [PDF]

Marginal Causal Consistency in Constraint-based Causal Learning

Anna Roumpelaki, Giorgos Borboudakis, Sofia Triantafillou and Ioannis Tsamardinos

[Abstract] [PDF]

Causal Inference for Recommendation

Dawen Liang, Laurent Charlin and David Blei

[Abstract] [PDF]

Pairwise Cluster Comparison for Learning Latent Variable Models

Nuaman Asbeh and Boaz Lerner

[Abstract] [PDF]

Split-door Criterion for Causal Identification: Natural Experiments with Testable Assumptions

Amit Sharma, Jake Hofman and Duncan Watts

[Abstract] [PDF]

Validating Causal Models

Dustin Tran, Francisco J. R. Ruiz, Susan Athey and David M. Blei

[Abstract] [PDF]