Kangcheng Lin

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All published works

Action	Title	Year	Authors
+ PDF Chat	A holistic approach to interpretability in financial lending: Models, visualizations, and summary-explanations	2021	Chaofan Chen Kangcheng Lin Cynthia Rudin Yaron Shaposhnik Sijia Wang Tong Wang
+	A Holistic Approach to Interpretability in Financial Lending: Models, Visualizations, and Summary-Explanations	2021	Chaofan Chen Kangcheng Lin Cynthia Rudin Yaron Shaposhnik Sijia Wang Tong Wang
+	An Interpretable Model with Globally Consistent Explanations for Credit Risk	2018	Chaofan Chen Kangcheng Lin Cynthia Rudin Yaron Shaposhnik Sijia Wang Tong Wang

Common Coauthors

Coauthor	Papers Together
Cynthia Rudin	3
Yaron Shaposhnik	3
Sijia Wang	3
Tong Wang	3
Chaofan Chen	3

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	Optimized Risk Scores	2017	Berk Ustun Cynthia Rudin	3
+ PDF Chat	Supersparse linear integer models for optimized medical scoring systems	2015	Berk Ustun Cynthia Rudin	3
+ PDF Chat	A Survey of Methods for Explaining Black Box Models	2018	Riccardo Guidotti Anna Monreale Salvatore Ruggieri Franco Turini Fosca Giannotti Dino Pedreschi	3
+	Forecasting remaining useful life: Interpretable deep learning approach via variational Bayesian inferences	2019	Mathias Kraus Stefan Feuerriegel	2
+	An Interpretable Model with Globally Consistent Explanations for Credit Risk	2018	Chaofan Chen Kangcheng Lin Cynthia Rudin Yaron Shaposhnik Sijia Wang Tong Wang	2
+	The fused lasso penalty for learning interpretable medical scoring systems	2017	Nataliya Sokolovska Yann Chevaleyre Karine Clément Jean‐Daniel Zucker	2
+	Learning Optimized Risk Scores	2019	Berk Ustun Cynthia Rudin	2
+ PDF Chat	Accurate intelligible models with pairwise interactions	2013	Yin Lou Rich Caruana Johannes Gehrke Giles Hooker	2
+	The Age of Secrecy and Unfairness in Recidivism Prediction	2020	Cynthia Rudin Caroline Wang Beau Coker	2
+	An Optimization Approach to Learning Falling Rule Lists	2017	Chaofan Chen Cynthia Rudin	1
+	A threshold of ln <i>n</i> for approximating set cover (preliminary version)	1996	Uriel Feige	1
+	Interpretable Credit Application Predictions With Counterfactual Explanations	2018	Rory Mc Grath Luca Costabello Chan Le Van Paul Sweeney Farbod Kamiab Zhao Shen Freddy Lécué	1
+ PDF Chat	Proceedings of the 25th international conference on Machine learning - ICML '08	2008		1
+	Interpretable and Explorable Approximations of Black Box Models	2017	Himabindu Lakkaraju Ece Kamar Rich Caruana Jure Leskovec	1
+	Local Rule-Based Explanations of Black Box Decision Systems.	2018	Riccardo Guidotti Anna Monreale Salvatore Ruggieri Dino Pedreschi Franco Turini Fosca Giannotti	1
+	Explainable Neural Networks based on Additive Index Models	2018	Joel Vaughan Agus Sudjianto Erind Brahimi Jie Chen Vijayan N. Nair	1
+ PDF Chat	RuleMatrix: Visualizing and Understanding Classifiers with Rules	2018	Ming Yao Huamin Qu Enrico Bertini	1
+	"Why Should You Trust My Explanation?" Understanding Uncertainty in LIME Explanations	2019	Yujia Zhang Kuangyan Song Yiming Sun Sarah Tan Madeleine Udell	1
+	RuleMatrix: Visualizing and Understanding Classifiers with Rules	2018	Ming Yao Huamin Qu Enrico Bertini	1
+	"Why Should I Trust You?": Explaining the Predictions of Any Classifier	2016	Marco Túlio Ribeiro Sameer Singh Carlos Guestrin	1