2016 Code Plenary Session 3 2016 Code Plenary Session 3
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2016 Code Plenary Session 3 2016 Code Plenary Session 3 Information Guide
Overview to 2016 Code Plenary Session 3 2016 Code Plenary Session 3

Machine Learning, Causal Inference, and Estimating Heterogeneous Treatment Effects. Jas Sekhon (UC Berkeley) Machine ... Matrix Completion Methods for Causal Panel Data Models. Guido Imbens (Stanford) Digital Experimentation for Multi-Channel ... Estimation and Evaluation of Optimal Policies. Susan Athey (Stanford University) Escaping from Government and Corporate ... When Randomized Experiments are Plentiful. Dean Eckles (MIT) Insights from Behavioral Economics for Consumer Finance ... Optimal Team Construction for a Complex Task. Duncan Watts (Microsoft) Toward Real-Time Measures of Poverty and ... ... have in terms of law and jurisprudence for example alpena
The Necessity for Causation is Overstated. Sendhil Mullainathan (Harvard University) Correlation Rather than Causation? Efficient Exponential Digital Experimentation. John Langford (Microsoft) Do Crowds have the Wisdom to Self Organize? Challenging Problems in Online Controlled Experiments. Ron Kohavi (Microsoft). Incentive Compatible Experimental Design. The Economic and Social Commission for Asia and the Pacific (ESCAP) will convene the third
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Last Updated: June 16, 2026
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