Sarah Tan
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“No fracking way!” Documentary film, discursive opportunity, and local opposition against hydraulic fracturing in the United States, 2010 to 2013
IB Vasi, ET Walker, JS Johnson, HF Tan
American Sociological Review 80 (5), 934-959, 2015
Distill-and-Compare: Auditing Black-Box Models Using Transparent Model Distillation
S Tan, R Caruana, G Hooker, Y Lou
Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society, 2018
Considerations When Learning Additive Explanations for Black-Box Models
S Tan, G Hooker, P Koch, A Gordo, R Caruana
arXiv preprint arXiv:1801.08640 3, 2018
"Why Should You Trust My Explanation?" Understanding Uncertainty in LIME Explanations
Y Zhang, K Song, Y Sun, S Tan, M Udell
ICML 2019 AI for Social Good Workshop, 2019
Tree space prototypes: Another look at making tree ensembles interpretable
S Tan, M Soloviev, G Hooker, MT Wells
Proceedings of the 2020 ACM-IMS on Foundations of Data Science Conference, 23-34, 2020
Investigating Human+ Machine Complementarity: A Case Study on Recidivism
S Tan, J Adebayo, K Inkpen, E Kamar
arXiv preprint arXiv:1808.09123, 2018
How Interpretable and Trustworthy are GAMs?
CH Chang, S Tan, B Lengerich, A Goldenberg, R Caruana
Proceedings of the 27th ACM SIGKDD International Conference on Knowledge …, 2021
Axiomatic Interpretability for Multiclass Additive Models
X Zhang, S Tan, P Koch, Y Lou, U Chajewska, R Caruana
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019
Do I Look Like a Criminal? Examining how Race Presentation Impacts Human Judgement of Recidivism
K Mallari, K Inkpen, P Johns, S Tan, D Ramesh, E Kamar
Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems …, 2020
Purifying Interaction Effects with the Functional ANOVA: An Efficient Algorithm for Recovering Identifiable Additive Models
B Lengerich, S Tan, CH Chang, G Hooker, R Caruana
International Conference on Artificial Intelligence and Statistics, 2402-2412, 2020
A Bayesian Evidence Synthesis Approach to Estimate Disease Prevalence in Hard-To-Reach Populations: Hepatitis C in New York City
S Tan, S Makela, D Heller, K Konty, S Balter, T Zheng, JH Stark
Epidemics 23 (June 2018), 96-109, 2018
Interpretable Approaches to Detect Bias in Black-Box Models
S Tan
Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society …, 2018
Efficient Heterogeneous Treatment Effect Estimation With Multiple Experiments and Multiple Outcomes
L Yao, C Lo, I Nir, S Tan, A Evnine, A Lerer, A Peysakhovich
arXiv preprint arXiv:2206.04907, 2022
A Double Parametric Bootstrap Test for Topic Models
S Seto, S Tan, G Hooker, MT Wells
NeurIPS 2017 Interpretability Symposium, 2017
Using Explainable Boosting Machines (EBMs) to Detect Common Flaws in Data
Z Chen, S Tan, H Nori, K Inkpen, Y Lou, R Caruana
Machine Learning and Principles and Practice of Knowledge Discovery in …, 2022
Interpretable Personalized Experimentation
H Wu, S Tan, W Li, M Garrard, A Obeng, D Dimmery, S Singh, H Wang, ...
Proceedings of the 28th ACM SIGKDD International Conference on Knowledge …, 2022
Probabilistic Matching: Incorporating Uncertainty to Correct for Selection Bias
HF Tan, GJ Hooker, MT Wells
NeurIPS 2016 Causal Inference Workshop, 2016
Two Ways of Modeling Hospital Readmissions: Mixed and Marginal Models
HF Tan, R Low, S Ito, R Gregory, L Bielory, V Dunn
Proceedings of the Joint Statistical Meetings, 2013
Using PROC GENMOD to Investigate Drug Interactions: Beta Blockers and Beta Agonists and Their Association with Hospital Admissions
HF Tan, R Low, S Ito, R Gregory, V Dunn
Proceedings of SAS Global Forum, 2013
Hospital Readmission Rates: Related To Ed Volume, Population, And Economic Variables
RB Low, S Ito, R Gregory, L Rassi, HF Tan, C Jacobs
Academic Emergency Medicine 19 (4), S208-S209, 2012
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