• case-insensitive prefix search: default
  e.g., sig matches "SIGIR" as well as "signal"
• exact word search: append dollar sign ($) to word
  e.g., graph$ matches "graph", but not "graphics"
• boolean and: separate words by space
  e.g., codd model
• boolean or: connect words by pipe symbol (|)
  e.g., graph|network

Update May 7, 2017: Please note that we had to disable the phrase search operator (.) and the boolean not operator (-) due to technical problems. For the time being, phrase search queries will yield regular prefix search result, and search terms preceded by a minus will be interpreted as regular (positive) search terms.

found 150 matches

• 2024
• 
  Tomas M. Bosschieter, Zifei Xu, Hui Lan, Benjamin J. Lengerich, Harsha Nori, Ian S. Painter, Vivienne Souter, Rich Caruana:
  Interpretable Predictive Models to Understand Risk Factors for Maternal and Fetal Outcomes. J. Heal. Informatics Res. 8(1): 65-87 (2024)
• 
  Chandan Singh, Jeevana Priya Inala, Michel Galley, Rich Caruana, Jianfeng Gao:
  Rethinking Interpretability in the Era of Large Language Models. CoRR abs/2402.01761 (2024)
• 
  Sebastian Bordt, Benjamin J. Lengerich, Harsha Nori, Rich Caruana:
  Data Science with LLMs and Interpretable Models. CoRR abs/2402.14474 (2024)
• 
  Sebastian Bordt, Harsha Nori, Rich Caruana:
  Elephants Never Forget: Testing Language Models for Memorization of Tabular Data. CoRR abs/2403.06644 (2024)
• 2023
• 
  Sarah Tan, Giles Hooker, Paul Koch, Albert Gordo, Rich Caruana:
  Considerations when learning additive explanations for black-box models. Mach. Learn. 112(9): 3333-3359 (2023)
• 
  Zijie J. Wang, Jennifer Wortman Vaughan, Rich Caruana, Duen Horng Chau:
  GAM Coach: Towards Interactive and User-centered Algorithmic Recourse. CHI 2023: 835:1-835:20
• 
  Zhi Chen, Sarah Tan, Urszula Chajewska, Cynthia Rudin, Rich Caruana:
  Missing Values and Imputation in Healthcare Data: Can Interpretable Machine Learning Help? CHIL 2023: 86-99
• 
  Zijie J. Wang, Jennifer Wortman Vaughan, Rich Caruana, Duen Horng Chau:
  GAM Coach: Towards Interactive and User-centered Algorithmic Recourse. CoRR abs/2302.14165 (2023)
• 
  Zhi Chen, Sarah Tan, Urszula Chajewska, Cynthia Rudin, Rich Caruana:
  Missing Values and Imputation in Healthcare Data: Can Interpretable Machine Learning Help? CoRR abs/2304.11749 (2023)
• 
  Daniel Schug, Sai S. Yerramreddy, Rich Caruana, Craig Greenberg, Justyna P. Zwolak:
  Extending Explainable Boosting Machines to Scientific Image Data. CoRR abs/2305.16526 (2023)
• 
  Alexander Peysakhovich, Rich Caruana, Yin Aphinyanaphongs:
  Diagnosis Uncertain Models For Medical Risk Prediction. CoRR abs/2306.17337 (2023)
• 
  Benjamin J. Lengerich, Sebastian Bordt, Harsha Nori, Mark E. Nunnally, Yin Aphinyanaphongs, Manolis Kellis, Rich Caruana:
  LLMs Understand Glass-Box Models, Discover Surprises, and Suggest Repairs. CoRR abs/2308.01157 (2023)
• 
  Tomas M. Bosschieter, Zifei Xu, Hui Lan, Benjamin J. Lengerich, Harsha Nori, Ian S. Painter, Vivienne Souter, Rich Caruana:
  Interpretable Predictive Models to Understand Risk Factors for Maternal and Fetal Outcomes. CoRR abs/2310.10203 (2023)
• 
  Odelia Melamed, Rich Caruana:
  Explaining high-dimensional text classifiers. CoRR abs/2311.13454 (2023)
• 2022
• 
  Du Wang, Sang Ho Lee, Huaizhi Geng, Haoyu Zhong, John Plastaras, Andrzej Wojcieszynski, Richard Caruana, Ying Xiao:
  Interpretable machine learning for predicting pathologic complete response in patients treated with chemoradiation therapy for rectal adenocarcinoma. Frontiers Artif. Intell. 5 (2022)
• 
  Benjamin J. Lengerich, Mark E. Nunnally, Yin Aphinyanaphongs, Caleb Ellington, Rich Caruana:
  Automated interpretable discovery of heterogeneous treatment effectiveness: A COVID-19 case study. J. Biomed. Informatics 130: 104086 (2022)
• 
  Benjamin J. Lengerich, Eric P. Xing, Rich Caruana:
  Dropout as a Regularizer of Interaction Effects. AISTATS 2022: 7550-7564
• 
  Fengshi Niu, Harsha Nori, Brian Quistorff, Rich Caruana, Donald Ngwe, Aadharsh Kannan:
  Differentially Private Estimation of Heterogeneous Causal Effects. CLeaR 2022: 618-633
• 
  Chun-Hao Chang, Rich Caruana, Anna Goldenberg:
  NODE-GAM: Neural Generalized Additive Model for Interpretable Deep Learning. ICLR 2022
• 
  Rich Caruana, Harsha Nori:
  Why Data Scientists Prefer Glassbox Machine Learning: Algorithms, Differential Privacy, Editing and Bias Mitigation. KDD 2022: 4776-4777
• 
  Zijie J. Wang, Alex Kale, Harsha Nori, Peter Stella, Mark E. Nunnally, Duen Horng Chau, Mihaela Vorvoreanu, Jennifer Wortman Vaughan, Rich Caruana:
  Interpretability, Then What? Editing Machine Learning Models to Reflect Human Knowledge and Values. KDD 2022: 4132-4142
• 
  Fengshi Niu, Harsha Nori, Brian Quistorff, Rich Caruana, Donald Ngwe, Aadharsh Kannan:
  Differentially Private Estimation of Heterogeneous Causal Effects. CoRR abs/2202.11043 (2022)
• 
  Zijie J. Wang, Alex Kale, Harsha Nori, Peter Stella, Mark E. Nunnally, Duen Horng Chau, Mihaela Vorvoreanu, Jennifer Wortman Vaughan, Rich Caruana:
  Interpretability, Then What? Editing Machine Learning Models to Reflect Human Knowledge and Values. CoRR abs/2206.15465 (2022)
• 
  Tomas M. Bosschieter, Zifei Xu, Hui Lan, Benjamin J. Lengerich, Harsha Nori, Kristin Sitcov, Vivienne Souter, Rich Caruana:
  Using Interpretable Machine Learning to Predict Maternal and Fetal Outcomes. CoRR abs/2207.05322 (2022)
• 
  Benjamin J. Lengerich, Mark E. Nunnally, Yin Aphinyanaphongs, Rich Caruana:
  Estimating Discontinuous Time-Varying Risk Factors and Treatment Benefits for COVID-19 with Interpretable ML. CoRR abs/2211.08991 (2022)
• 2021
• 
  Alex Okeson, Rich Caruana, Nick Craswell, Kori Inkpen, Scott M. Lundberg, Harsha Nori, Hanna M. Wallach, Jennifer Wortman Vaughan:
  Summarize with Caution: Comparing Global Feature Attributions. IEEE Data Eng. Bull. 44(4): 14-27 (2021)
• 
  Rich Caruana, Benjamin J. Lengerich, Yindalon Aphinyanaphongs:
  Data-Driven Patterns in Protective Effects of Ibuprofen and Ketorolac on Hospitalized Covid-19 Patients. AMIA 2021
• 
  Harsha Nori, Rich Caruana, Zhiqi Bu, Judy Hanwen Shen, Janardhan Kulkarni:
  Accuracy, Interpretability, and Differential Privacy via Explainable Boosting. ICML 2021: 8227-8237
• 
  Chun-Hao Chang, Sarah Tan, Benjamin J. Lengerich, Anna Goldenberg, Rich Caruana:
  How Interpretable and Trustworthy are GAMs? KDD 2021: 95-105
• 
  Harmanpreet Kaur, Harsha Nori, Samuel Jenkins, Rich Caruana, Hanna M. Wallach, Jennifer Wortman Vaughan:
  Interpreting Interpretability: Understanding Data Scientists' Use of Interpretability Tools for Machine Learning. DaSH@KDD 2021

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