Jorge Gallego

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All published works

Action	Title	Year	Authors
+ PDF Chat	Predicting politicians’ misconduct: Evidence from Colombia	2022	Jorge Gallego Mounu Prem Juan F. Vargas
+	Preventing rather than punishing: An early warning model of malfeasance in public procurement	2020	Jorge Gallego Gonzalo Rivero Juan Diego Sánchez Martínez
+ PDF Chat	What Predicts Corruption?	2019	Emanuele Colonnelli Jorge Gallego Mounu Prem

Common Coauthors

Coauthor	Papers Together
Mounu Prem	2
Emanuele Colonnelli	1
Juan Diego Sánchez Martínez	1
Juan F. Vargas	1
Gonzalo Rivero	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+ PDF Chat	High-Dimensional Methods and Inference on Structural and Treatment Effects	2014	Alexandre Belloni Victor Chernozhukov Christian Hansen	3
+	Regression Shrinkage and Selection Via the Lasso	1996	Robert Tibshirani	3
+	Preventing rather than punishing: An early warning model of malfeasance in public procurement	2020	Jorge Gallego Gonzalo Rivero Juan Diego Sánchez Martínez	2
+	Predicting and explaining corruption across countries: A machine learning approach	2019	Marcio Salles Melo Lima Dursun Delen	2
+ PDF Chat	Prediction Policy Problems	2015	Jon Kleinberg Jens Ludwig Sendhil Mullainathan Ziad Obermeyer	2
+	Super Learner	2007	Mark J. van der Laan Eric C. Polley Alan Hubbard	2
+	Predicting Public Corruption with Neural Networks: An Analysis of Spanish Provinces	2017	Félix J. López‐Iturriaga Iván Pastor Sanz	2
+	The Elements of Statistical Learning	2001	Trevor Hastie J. Friedman Robert Tibshirani	2
+ PDF Chat	Additive logistic regression: a statistical view of boosting (With discussion and a rejoinder by the authors)	2000	Jerome H. Friedman Trevor Hastie Robert Tibshirani	2
+ PDF Chat	The Selective Labels Problem	2017	Himabindu Lakkaraju Jon Kleinberg Jure Leskovec Jens Ludwig Sendhil Mullainathan	1
+	Techniques for Interpretable Machine Learning	2018	Mengnan Du Ninghao Liu Xia Hu	1
+	All Models are Wrong but many are Useful: Variable Importance for Black-Box, Proprietary, or Misspecified Prediction Models, using Model Class Reliance	2018	Aaron Fisher Cynthia Rudin Francesca Dominici	1
+ PDF Chat	What Predicts Corruption?	2019	Emanuele Colonnelli Jorge Gallego Mounu Prem	1
+	Proceedings of the 25th international conference on Machine learning	2008	William W. Cohen Andrew McCallum Sam T. Roweis	1
+	Machine Learning Methods That Economists Should Know About	2019	Susan Athey Guido W. Imbens	1
+ PDF Chat	Program Evaluation and Causal Inference With High-Dimensional Data	2017	Alexandre Belloni Victor Chernozhukov I. Fern�ndez-Val Christian Hansen	1
+ PDF Chat	A Survey of Methods for Explaining Black Box Models	2018	Riccardo Guidotti Anna Monreale Salvatore Ruggieri Franco Turini Fosca Giannotti Dino Pedreschi	1
+	Learning to Explain: An Information-Theoretic Perspective on Model Interpretation	2018	Jianbo Chen Le Song Martin J. Wainwright Michael I. Jordan	1
+ PDF Chat	Techniques for interpretable machine learning	2019	Mengnan Du Ninghao Liu Xia Hu	1
+ PDF Chat	The Promise and Pitfalls of Conflict Prediction: Evidence from Colombia and Indonesia	2019	Samuel Bazzi Robert Blair Christopher Blattman Oeindrila Dube Matthew Gudgeon Richard M. Peck	1
+	Regularization Paths for Generalized Linear Models via Coordinate Descent	2010	Jerome H. Friedman Trevor Hastie Robert Tibshirani	1
+	gbm: Generalized Boosted Regression Models	2003	Greg Ridgeway Gbm Developers	1
+	Statistical Learning with Sparsity	2015	Trevor Hastie Robert Tibshirani Martin J. Wainwright	1
+ PDF Chat	Statistical Modeling: The Two Cultures (with comments and a rejoinder by the author)	2001	Leo Breiman	1
+	Regularization Paths for Generalized Linear Models via Coordinate Descent.	2010	Jerome H. Friedman Trevor Hastie Rob Tibshirani	1
+ PDF Chat	SMOTE: Synthetic Minority Over-sampling Technique	2002	Nitesh V. Chawla Kevin W. Bowyer Lawrence Hall W. Philip Kegelmeyer	1
+	Program evaluation and causal inference with high-dimensional data	2016	Alexandre Belloni Victor Chernozhukov Iván Fernández‐Val Christian Hansen	1
+	Model-Agnostic Interpretability of Machine Learning	2016	Marco Túlio Ribeiro Sameer Singh Carlos Guestrin	1
+	Towards A Rigorous Science of Interpretable Machine Learning	2017	Finale Doshi‐Velez Been Kim	1
+ PDF Chat	What Can We Learn from Predictive Modeling?	2017	Skyler Cranmer Bruce Desmarais	1