We invite submissions of contributions to The NeurIPS 2021 workshop on Causal Inference Challenges in Sequential Decision Making: Bridging Theory and Practice.

Workshop website: https://sites.google.com/view/causal-sequential-decisions

Submission deadline: September 30th, 2021 (AoE)
Submit at: https://cmt3.research.microsoft.com/CSDNeurIPS2021


-- Workshop Abstract --

Sequential decision-making problems appear in settings as varied as healthcare, e-commerce, operations management, and policymaking, and depending on the context these can have very varied features that make each problem unique. Problems can involve online learning or offline data, known cost structures or unknown counterfactuals, continuous actions with or without constraints or finite or combinatorial actions, stationary environments or environments with dynamic agents, utilitarian considerations or fairness or equity considerations. More and more, causal inference and discovery and adjacent statistical theories have come to bear on such problems, from the early work on longitudinal causal inference from the last millenium up to recent developments in bandit algorithms and inference, dynamic treatment regimes, both online and offline reinforcement learning, interventions in general causal graphs and discovery thereof, and more. While the interaction between these theories has grown, expertise is spread across many different disciplines, including CS/ML, biostatistics/healthcare, economics/evidence-based policymaking, applications in the industry such as online advertising, and ethics/law.

The primary purpose of this workshop is to convene both experts, practitioners, and interested researchers from a wide range of backgrounds to discuss recent developments around causal inference in sequential decision making and the avenues forward on the topic, especially ones that bring together ideas from different fields. The all-virtual nature of this year's NeurIPS workshop makes it particularly felicitous to such an assembly. The workshop will combine invited talks and panels by a diverse group of researchers and practitioners from both academia and industry together with contributed talks and town-hall Q&A.


-- Topics for submissions --

We invite contributions on any topic related to the subject of the workshop, including but not limited to the following topics:
- Dynamic treatment regimes
- Causal inference and discovery from longitudinal and panel data
- Unmeasured confounding in sequential decisions and sensitivity analyses
- Causality in dynamical systems
- Econometric/structural estimation in sequential settings
- Off-policy evaluation and logged bandits
- Offline reinforcement learning and imitation learning
- A/B-testing and design of experiments
- Algorithmic fairness in dynamic environments
- Causal graphs with multiple and/or sequential interventions
- Online allocation and online linear programs
- Data-driven inverse optimization in sequential settings
- Applications, including in healthcare, e-commerce, and policymaking


-- Formatting instructions and submission process --

Submissions should use the NeurIPS 2021 template, and be 2-6 pages (plus as many pages as necessary for references and supplementary material). Submissions of extended abstracts of longer work is allowed and, after acceptance, these may may directly link to the longer version on a preprint server (e.g., on arXiv). Submissions should otherwise be anonymized during the review process. We remark that looking at supplementary material is at the discretion of the reviewers.

All submissions will be peer-reviewed. There are no official archival proceedings. Contributors can still publish accepted work in archival journals or conferences. The submissions will only be posted on the workshop website for presentation purposes. Authors will have the opportunity to link to a version on a preprint server. A subset of submissions will be invited for a spotlight talk, and the remaining will be invited to present at the poster session.