7th Causality Workshop: Learning, Inference, and Decision-Making
Tuesday, August 15, 2017
Sydney, Australia
Introduction
Causality shapes how we view, understand, and react to the world around us. It’s a key ingredient in building AI systems that are autonomous and can act efficiently in complex and uncertain environments. It’s also important to the process of scientific discovery since it underpins how explanations are constructed and the scientific method.
Not surprisingly, the tasks of learning and reasoning with causal-effect relationships have attracted great interest in the artificial intelligence and machine learning communities. This effort has led to a very general theoretical and algorithmic understanding of what causality means and under what conditions it can be inferred. These results have started to percolate through more applied fields that generate the bulk of the data currently available, ranging from genetics to medicine, from psychology to economics.
This one-day workshop will explore causal inference in a broad sense through a set of invited talks, open problems sessions, presentations, and a poster session. In this workshop, we will focus on the foundational side of causality on the one hand, and challenges presented by practical applications on the other. By and large, we welcome contributions from all areas relating to the study of causality.
We encourage co-submission of (full) papers that have been submitted to the main UAI 2017 conference. This workshop is a sequel to a successful predecessor at UAI 2016.
Invited Speakers
David Danks, Carnegie Mellon University
Important Dates
| August 15 | Workshop (last day of the UAI 2017 main conference, August 11-15) |
Organizers
Elias Bareinboim, Purdue (Chair)
Kun Zhang, CMU
Caroline Uhler, MIT
Jiji Zhang, Lingnan University
Dominik Janzing, MPI Tubingen
Program committee
Jeff Adams (CMU)
Krzysztof Chalupka (Caltech)
Tony Chan (MPI Tubingen)
Bryant Chen (IBM Research)
Tianjiao Chu (University of Pittsburgh)
Tom Claassen (Radboud University)
Frederick Eberhardt (Caltech)
Seyedjalal Etesami (UIUC)
Robin Evans (University of Oxford)
Philipp Geiger (MPI Tubingen)
Mingming Gong (CMU)
Antti Hyttinen (HIIT-University of Helsinki)
Yoshinobu Kawahara (Osaka University)
Murat Kocaoglu (UT Austin)
Manabu Kuroki (Yokohama National University)
Sanghack Lee (Penn State)
Karthika Mohan (UCLA)
Joris Mooij (University of Amsterdam)
Ridho Rahmadi (Radboud University)
Roland Ramsahai
Joe Ramsey (CMU)
Garvesh Raskutti (Univ. of Wisconsin-Madison)
Ruben Sanches (CMU)
Karthikeyan Shanmugam (IBM Research)
Shohei Shimizu (Osaka University)
Ricardo Silva (UCL)
Peter Stojanov (CMU)
Eric Strobl (University of Pittsburgh)