Sarah Tan

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 25

Top Topics

Multiclass Problems

Additive Models

Top Venues

Publications

Rithesh Murthy, Liangwei Yang, Juntao Tan, Tulika Manoj Awalgaonkar, Yilun Zhou, Shelby Heinecke, Sachin Desai, Jason Wu, Ran Xu, Sarah Tan, Jianguo Zhang, Zhiwei Liu, Shirley Kokane, Zuxin Liu, Ming Zhu, Huan Wang, Caiming Xiong, Silvio Savarese
MobileAIBench: Benchmarking LLMs and LMMs for On-Device Use Cases. CoRR (2024)
Sarah Tan, Giles Hooker, Paul Koch, Albert Gordo, Rich Caruana
Considerations when learning additive explanations for black-box models. Mach. Learn. 112 (9) (2023)
Fulton Wang, Julius Adebayo, Sarah Tan, Diego García-Olano, Narine Kokhlikyan
Error Discovery By Clustering Influence Embeddings. NeurIPS (2023)
Fulton Wang, Julius Adebayo, Sarah Tan, Diego García-Olano, Narine Kokhlikyan
Error Discovery by Clustering Influence Embeddings. CoRR (2023)
Zhi Chen, Sarah Tan, Urszula Chajewska, Cynthia Rudin, Rich Caruana
Missing Values and Imputation in Healthcare Data: Can Interpretable Machine Learning Help? CHIL (2023)
Zhi Chen, Sarah Tan, Urszula Chajewska, Cynthia Rudin, Rich Caruana
Missing Values and Imputation in Healthcare Data: Can Interpretable Machine Learning Help? CoRR (2023)
Mia Garrard, Hanson Wang, Ben Letham, Shaun Singh, Abbas Kazerouni, Sarah Tan, Zehui Wang, Yin Huang, Yichun Hu, Chad Zhou, Norm Zhou, Eytan Bakshy
Practical Policy Optimization with Personalized Experimentation. CoRR (2023)
Leon Yao, Caroline Lo, Israel Nir, Sarah Tan, Ariel Evnine, Adam Lerer, Alex Peysakhovich
Efficient Heterogeneous Treatment Effect Estimation With Multiple Experiments and Multiple Outcomes. CoRR (2022)
Han Wu, Sarah Tan, Weiwei Li, Mia Garrard, Adam Obeng, Drew Dimmery, Shaun Singh, Hanson Wang, Daniel Jiang, Eytan Bakshy
Interpretable Personalized Experimentation. KDD (2022)
Chun-Hao Chang, Sarah Tan, Benjamin Lengerich, Anna Goldenberg, Rich Caruana
How Interpretable and Trustworthy are GAMs? KDD (2021)
Han Wu, Sarah Tan, Weiwei Li, Mia Garrard, Adam Obeng, Drew Dimmery, Shaun Singh, Hanson Wang, Daniel Jiang, Eytan Bakshy
Distilling Heterogeneity: From Explanations of Heterogeneous Treatment Effect Models to Interpretable Policies. CoRR (2021)
Zhi Chen, Sarah Tan, Harsha Nori, Kori Inkpen, Yin Lou, Rich Caruana
Using Explainable Boosting Machines (EBMs) to Detect Common Flaws in Data. PKDD/ECML Workshops (1) (2021)
Sarah Tan, Matvey Soloviev, Giles Hooker, Martin T. Wells
Tree Space Prototypes: Another Look at Making Tree Ensembles Interpretable. FODS (2020)
Keri Mallari, Kori Inkpen, Paul Johns, Sarah Tan, Divya Ramesh, Ece Kamar
Do I Look Like a Criminal? Examining how Race Presentation Impacts Human Judgement of Recidivism. CoRR (2020)
Keri Mallari, Kori Inkpen, Paul Johns, Sarah Tan, Divya Ramesh, Ece Kamar
Do I Look Like a Criminal? Examining how Race Presentation Impacts Human Judgement of Recidivism. CHI (2020)
Chun-Hao Chang, Sarah Tan, Benjamin Lengerich, Anna Goldenberg, Rich Caruana
How Interpretable and Trustworthy are GAMs? CoRR (2020)
Benjamin Lengerich, Sarah Tan, Chun-Hao Chang, Giles Hooker, Rich Caruana
Purifying Interaction Effects with the Functional ANOVA: An Efficient Algorithm for Recovering Identifiable Additive Models. AISTATS (2020)
Benjamin Lengerich, Sarah Tan, Chun-Hao Chang, Giles Hooker, Rich Caruana
Purifying Interaction Effects with the Functional ANOVA: An Efficient Algorithm for Recovering Identifiable Additive Models. CoRR (2019)
Xuezhou Zhang, Sarah Tan, Paul Koch, Yin Lou, Urszula Chajewska, Rich Caruana
Axiomatic Interpretability for Multiclass Additive Models. KDD (2019)
Xuezhou Zhang, Sarah Tan, Paul Koch, Yin Lou, Urszula Chajewska, Rich Caruana
Interpretability is Harder in the Multiclass Setting: Axiomatic Interpretability for Multiclass Additive Models. CoRR (2018)
Sarah Tan
Interpretable Approaches to Detect Bias in Black-Box Models. AIES (2018)
Sarah Tan, Rich Caruana, Giles Hooker, Yin Lou
Distill-and-Compare: Auditing Black-Box Models Using Transparent Model Distillation. AIES (2018)
Sarah Tan, Julius Adebayo, Kori Inkpen, Ece Kamar
Investigating Human + Machine Complementarity for Recidivism Predictions. CoRR (2018)
Sarah Tan, Rich Caruana, Giles Hooker, Albert Gordo
Transparent Model Distillation. CoRR (2018)
Sarah Tan, Rich Caruana, Giles Hooker, Yin Lou
Detecting Bias in Black-Box Models Using Transparent Model Distillation. CoRR (2017)