What If? Inference and Learning of Hypothetical and Counterfactual Interventions in Complex Systems
A NIPS 2016 Workshop Centre Convencions Internacional Barcelona, Barcelona, Spain December 10th 2016 https://sites.google.com/site/whatif2016nips/ DESCRIPTION One of the promises of Big Data is its potential to answer "what if?" questions in digital, natural and social systems. Whether we speak of genetic interactions in a cell, passengers commuting in railways and roads, recommender systems matching users to ads, or understanding contagion in social networks, such systems are composed of many interacting components that suggest that learning to control them or understanding the effect of shocks to a system is not an easy task. What if some railways are closed, what will passengers do? What if we incentivize a member of a social network to propagate an idea, how influential can they be? What if some genes in a cell are knocked-out, which phenotypes can we expect? Such questions need to be addressed via a combination of experimental and observational data, and require a careful approach to modelling heterogeneous datasets and structural assumptions concerning the causal relations among the components of the system. The workshop is aimed at bringing together research expertise from a variety of communities in machine learning, statistics, engineering, and the social, medical and natural sciences. It is an opportunity for methods for causal inference, reinforcement learning and game theory to be cross-fertilized with more traditional research in statistics and the real-world constraints found in practical applications. Ultimately, this can lead to new research platforms to aid the assessment of policies, shocks and experimental design methods in the discovery of breakthroughs in a variety of domains. CALL FOR CONTRIBUTIONS The 2016 "What if?" workshop welcomes contributions from a variety of perspectives from machine learning, statistics, economics and social sciences, among others. This includes, but it is not limited to, the following topics: - Combining experimental control and observational data - Bandit algorithms and reinforcement learning with explicit links to causal inference and counterfactual reasoning - Interfaces of agent-based systems and causal inference - Handling selection bias - Large-scale algorithms - Applications in online systems (e.g. search, recommendation, ad placement) - Applications in complex systems (e.g. cell biology, smart cities, computational social sciences) At the discretion of the organizers, some contributions will be assigned slots as short contributed talks and others will be presented as posters. FORMAT We suggest extended abstracts of 2 pages in the NIPS format, but no specific format is enforced. A maximum of 8 pages will be considered. PDF files only. SUBMISSION INSTRUCTIONS AND DEADLINE 31st of October, 23:59 GMT time. Please submit your PDF by email to whatif2016sub...@gmail.com ORGANIZERS Ricardo Silva, University College London John Shawe-Taylor, University College London Adith Swaminathan, Cornell University Thorsten Joachims, Cornell University
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