INFORMS Joural on Data Science

2022 - 2026

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Volume 1, issue 2, 2022

Weakly Supervised Multi-output Regression via Correlated Gaussian Processes pp. 115-137

Seokhyun Chung, Raed Al Kontar and Zhenke Wu

Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem pp. 138-155

Mochen Yang, Edward McFowland, Gordon Burtch and Gediminas Adomavicius

A Robust Approach to Quantifying Uncertainty in Matching Problems of Causal Inference pp. 156-171

Marco Morucci, Md. Noor-E-Alam and Cynthia Rudin

Visualization in Operations Management Research pp. 172-187

Rahul Basole, Elliot Bendoly, Aravind Chandrasekaran and Kevin Linderman

Commentary on “Visualization in Operations Management Research”: Incorporating Statistical Thinking into Visualization Practices for Decision Making in Operational Management pp. 188-191

Emi Tanaka, Wai Yin Leung and Dianne Cook

Commentary on “Visualization in Operations Management Research” pp. 192-193

Ben Shneiderman

Commentary on “Visualization in Operations Management Research” pp. 194-195

Ran Jin

Volume 1, issue 1, 2022

Congratulations, It’s Our Inaugural Issue! pp. 1-3

Galit Shmueli

Causal Decision Making and Causal Effect Estimation Are Not the Same…and Why It Matters pp. 4-16

Carlos Fernández-Loría and Foster Provost

Commentary on “Causal Decision Making and Causal Effect Estimation Are Not the Same…and Why It Matters”: On Loss Functions and Bias–Variance Tradeoffs in Causal Estimation and Decisions pp. 17-18

Dean Eckles

Commentary on “Causal Decision Making and Causal Effect Estimation Are Not the Same…and Why It Matters” pp. 19-20

Uri Shalit

Commentary on “Causal Decision Making and Causal Effect Estimation Are Not the Same… and Why It Matters” pp. 21-22

Edward McFowland

Rejoinder to “Causal Decision Making and Causal Effect Estimation Are Not the Same…and Why It Matters” pp. 23-26

Carlos Fernández-Loría and Foster Provost

Adapting Reinforcement Learning Treatment Policies Using Limited Data to Personalize Critical Care pp. 27-49

Matt Baucum, Anahita Khojandi, Rama Vasudevan and Robert Davis

STR: Seasonal-Trend Decomposition Using Regression pp. 50-62

Alexander Dokumentov and Rob Hyndman

Constructing Prediction Intervals Using the Likelihood Ratio Statistic pp. 63-80

Qinglong Tian, Daniel J. Nordman and William Q. Meeker

HeBERT and HebEMO: A Hebrew BERT Model and a Tool for Polarity Analysis and Emotion Recognition pp. 81-95

Avihay Chriqui and Inbal Yahav

The Future of Forecasting Competitions: Design Attributes and Principles pp. 96-113

Spyros Makridakis, Chris Fry, Fotios Petropoulos and Evangelos Spiliotis