2016 Code Plenary Session 3

2016 Code Plenary Session 3 Information Guide

1. Introduction to 2016 Code Plenary Session 3
2. Key Details
3. Recent Updates
4. Full Guide
5. Summary

Introduction to 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 ... When Randomized Experiments are Plentiful. Dean Eckles (MIT) Insights from Behavioral Economics for Consumer Finance ... Estimation and Evaluation of Optimal Policies. Susan Athey (Stanford University) Escaping from Government and Corporate ... ... have in terms of law and jurisprudence for example alpena Optimal Team Construction for a Complex Task. Duncan Watts (Microsoft) Toward Real-Time Measures of Poverty and ...

Key Details

Recent Updates

2017 CODE Plenary Session 3: Guido Imbens, Jim Manzi, and Bin Yu

GC2016: May 20 - Plenary Session 3 #UMCGC

GC2016: May 19 - Plenary Session 3

GMF2016 Plenary Session 3

2016 CODE Plenary Session 2: Dean Eckles and Antoinette Schoar

2016 CODE Plenary Session 1: Susan Athey and Catherine Tucker

Mr. Soh Kar Liang Pandey Plenary Session III Part 1 At GIPC 2016, New Delhi, India

SDG 16 Conference: PLENARY SESSION 3.2 - SDG 16 AS A FRAMEWORK FOR MOVING THE 2030 AGENDA FORWARD:

2018 CODE Plenary Session 3: Duncan Watts and Joshua Blumenstock

Full Guide

Data is compiled from public records and verified media reports.

Last Updated: June 15, 2026

Summary

Disclaimer: Disclaimer: Details estimates are based on publicly available data, media reports, and financial analysis. Actual numbers may vary.