CausalML 2018 : ICML / IJCAI / AAMAS Workshop on Machine Learning for Causal Inference, Counterfactual Prediction, and Autonomous Action
June 14~15, 2018, Stockholm
Scope & Topics
Many of the most impactful applications of machine learning are not just about prediction, but are about putting learning systems in control of selecting the right action at the right time. Examples of such systems range from search engines that act by displaying a ranking, to medical decision support systems, recommender systems, ad placement systems, conversational systems, automated trading platforms, computer games, and cyber-physical systems like self-driving cars. This focus on acting requires some causal understanding of the world, since actions are interventions that change the distribution of data unlike in standard prediction problems. This gives rise to challenging counterfactual and causal prediction problems. However, causality is only a means to an end - namely being able to take the right actions; one typically does not have the burden of providing strong proofs of causal discovery.
We solicit submission of novel research related to all aspects of causal inference, counterfactual prediction, and autonomous action. This includes, but is not limited to, the following topics:
Topics of Interest :
Important Dates
| Submission Deadline | : | May 16, 2018 |
| Authors Notification | : | |
| Final Manuscript Due | : |
User Name : advika
Posted 22-03-2018 on 18:07:28 AEDT