2017 CODE Plenary: Cutting-Edge Causal Inference & Digital Experimentation π
Join leading experts Guido Imbens, Jim Manzi, and Bin Yu as they explore advanced matrix completion techniques for causal panel data models and innovative digital experimentation strategies for multi-channel companies.
MIT Initiative on the Digital Economy
618 views β’ Nov 6, 2017
About this video
Matrix Completion Methods for Causal Panel Data Models. Guido Imbens (Stanford)
Digital Experimentation for Multi-Channel Companies. Jim Manzi (Applied Predictive Technologies)
Three Principles of Data Science: Predictability, Stability, and Computability. Bin Yu (UC Berkeley)
Session Chair: Sandy Pentland (MIT)
Digital Experimentation for Multi-Channel Companies. Jim Manzi (Applied Predictive Technologies)
Three Principles of Data Science: Predictability, Stability, and Computability. Bin Yu (UC Berkeley)
Session Chair: Sandy Pentland (MIT)
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618
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2
Duration
01:11:45
Published
Nov 6, 2017
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