Missing Values and Imputation in Healthcare Data: Can Interpretable Machine Learning Help?
Zhi Chen, Sarah Tan, Urszula Chajewska, Cynthia Rudin , Rich Caruana
Conference on Health, Inference, and Learning (CHIL) 2023 | June 2023
Rich Caruana
Senior Principal Researcher
Publications
Publications by Year
-
GAM Coach: Towards Interactive and User-Centered Algorithmic Recourse
Zijie J. Wang, Jennifer Wortman Vaughan, Rich Caruana, Duen Horng Chau
2023 ACM CHI Conference on Human Factors in Computing Systems (CHI 2023) | February 2023
-
Interpretability, Then What? Editing Machine Learning Models to Reflect Human Knowledge and Values
Zijie J. Wang, Alex Kale, Harsha Nori, Peter Stella, Mark E. Nunnally, Duen Horng Chau, Mihaela Vorvoreanu, Jennifer Wortman Vaughan, Rich Caruana
KDD 2022 | July 2022
Differentially Private Estimation of Heterogeneous Causal Effects
Fengshi Niu, Harsha Nori, Brian Quistorff, Rich Caruana, Donald Ngwe, Aadharsh Kannan
CLeaR 2022 | April 2022
Node-GAM: Neural Generalized Additive Model For Interpretable Deep Learning
Chun-Hao Chang, Rich Caruana, Anna Goldenberg
ICLR 2022 | April 2022
-
GAM Changer: Editing Generalized Additive Models with Interactive Visualization
Zijie J. Wang, Alex Kale, Harsha Nori, Peter Stella, Mark Nunnally, Duen Horng Chau, Mihaela Vorvoreanu, Jennifer Wortman Vaughan, Rich Caruana
2021 Neural Information Processing Systems | December 2021
Neural Additive Models: Interpretable Machine Learning with Neural Nets
Rishabh Agarwal, Levi Melnick, Xuezhou Zhang, Ben Lengerich, Rich Caruana, Geoffrey Hinton
NeurIPS 2021 | December 2021
Summarize with Caution: Comparing Global Feature Attributions
Alex Okeson, Rich Caruana, Nick Craswell, Kori Inkpen, Scott M. Lundberg, Harsha Nori, Hanna Wallach, Jennifer Wortman Vaughan
Bulletin of the IEEE Computer Society Technical Committee on Data Engineering | December 2021
Automated Interpretable Discovery of Heterogeneous Treatment Effectiveness: A Covid-19 Case Study
Benjamin J. Lengerich, Mark E. Nunally, Yin Aphinyanaphongs, Rich Caruana
November 2021
Extracting Clinician’s Goals by What-if Interpretable Modeling
Chun-Hao Chang, George Alexandru Adam, Rich Caruana, Anna Goldenberg
AISTATS 2022 | October 2021
In review
Dropout as a Regularizer of Interaction Effects
Benjamin Lengerich, Eric P. Xing, Rich Caruana
October 2021
How Interpretable and Trustworthy are GAMs
Chun-Hao Chang, Sarah Tan, Ben Lengerich, Anna Goldenberg, Rich Caruana
KDD 2021 | August 2021
Accuracy, Interpretability, and Differential Privacy via Explainable Boosting
Harsha Nori, Rich Caruana, Zhiqi Bu, Judy Hanwen Shen, Janardhan (Jana) Kulkarni
2021 International Conference on Machine Learning | July 2021
-
Purifying Interaction Effects with the Functional ANOVA: An Efficient Algorithm for Recovering Identifiable Additive Models
Benjamin Lengerich, Sarah Tan, Chun-Hao Chang, Giles Hooker, Rich Caruana
International Conference on Artificial Intelligence and Statistics (AISTATS) 2020 | August 2020
Interpreting Interpretability: Understanding Data Scientists’ Use of Interpretability Tools for Machine Learning
Harmanpreet Kaur, Harsha Nori, Samuel Jenkins, Rich Caruana, Hanna Wallach, Jennifer Wortman Vaughan
CHI 2020 | April 2020
CHI 2020 Honorable Mention Award
-
Efficient Forward Architecture Search
Hanzhang Hu, John Langford, Rich Caruana, Saurajit Mukherjee, Eric Horvitz, Debadeepta Dey
Thirty-third Conference on Neural Information Processing Systems (NeurIPS 2019) | December 2019
InterpretML: A Unified Framework for Machine Learning Interpretability
Harsha Nori, Samuel Jenkins, Paul Koch, Rich Caruana
September 2019
Axiomatic Interpretability for Multiclass Additive Models
Xuezhou Zhang, Sarah Tan, Paul Koch, Yin Lou, Urszula Chajewska, Rich Caruana
The 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD ’19) | August 2019
Gamut: A Design Probe to Understand How Data Scientists Understand Machine Learning Models
Fred Hohman, Andrew Head, Rich Caruana, Robert DeLIne, Steven Drucker
SIGCHI | May 2019
-
Identifying Unknown Unknowns in the Open World: Representations and Policies for Guided Exploration
Himabindu Lakkaraju, Ece Kamar, Rich Caruana, Eric Horvitz
Thirty-First AAAI Conference on Artificial Intelligence | December 2016
Improving Document Ranking with Dual Word Embeddings
Eric Nalisnick, Bhaskar Mitra, Nick Craswell, Rich Caruana
WWW'16 | April 2016
A Dual Embedding Space Model for Document Ranking
Bhaskar Mitra, Eric Nalisnick, Nick Craswell, Rich Caruana
February 2016
This paper is an extended evaluation and analysis of the model proposed in a poster to appear in WWW'16, April 11 - 15, 2016, Montreal, Canada.
-
Implicit Preference Labels for Learning Highly Selective Personalized Rankers
Paul N. Bennett, Milad Shokouhi, Rich Caruana
Proceedings of the 1st ACM SIGIR International Conference on the Theory of Information Retrieval (ICTIR 2015) | September 2015
Intelligible Models for HealthCare: Predicting Pneumonia Risk and Hospital 30-day Readmission
Rich Caruana, Paul Koch, Yin Lou, Marc Sturm , Johannes Gehrke, Noemie Elhadad
KDD'15, August 10-13, 2015, Sydney, NSW, Australia | August 2015
ISBN: 978-1-4503-3664-2/15/08
-
Active Learning with Model Selection
Alnur Ali, Rich Caruana, Ashish Kapoor
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence | July 2014
Gauss Meets Canadian Traveler: Shortest-Path Problems with Correlated Natural Dynamics
Debadeepta Dey, Andrey Kolobov, Rich Caruana, Ece Kamar, Eric Horvitz, Ashish Kapoor
AAMAS 2014 | May 2014
Structured Labeling for Facilitating Concept Evolution in Machine Learning
Todd Kulesza, Saleema Amershi, Rich Caruana, Danyel Fisher, Denis Charles
Proceedings of the Conference on Human Factors in Computing Systems (CHI 2014) | May 2014
Best Paper Award
-
Accurate Intelligible Models with Pairwise Interactions
Yin Lou , Rich Caruana, Giles Hooker , Johannes Gehrke
KDD'13, August 11-14, 2013, Chicago, Illinois, USA | August 2013
ISBN: 978-1-4503-2174-7/13/08
-
Learning Speaker, Addressee and Overlap Detection Models from Multimodal Streams
Oriol Vinyals, Dan Bohus, Rich Caruana
ICMI '12 Proceedings of the 14th ACM International Conference on Multimodal Interaction | October 2012
Intelligible Models for Classiï¬cation and Regression
Yin Lou, Rich Caruana, Johannes Gehrke
KDD'12, Beijing, China | August 2012
ISBN: 978-1-4503-1462-6
-
Learning Likely Locations
John Krumm, Rich Caruana, Scott Counts
January 2011
Publications by Research Area
-
Missing Values and Imputation in Healthcare Data: Can Interpretable Machine Learning Help?
Zhi Chen, Sarah Tan, Urszula Chajewska, Cynthia Rudin , Rich Caruana
Conference on Health, Inference, and Learning (CHIL) 2023 | June 2023
GAM Coach: Towards Interactive and User-Centered Algorithmic Recourse
Zijie J. Wang, Jennifer Wortman Vaughan, Rich Caruana, Duen Horng Chau
2023 ACM CHI Conference on Human Factors in Computing Systems (CHI 2023) | February 2023
Interpretability, Then What? Editing Machine Learning Models to Reflect Human Knowledge and Values
Zijie J. Wang, Alex Kale, Harsha Nori, Peter Stella, Mark E. Nunnally, Duen Horng Chau, Mihaela Vorvoreanu, Jennifer Wortman Vaughan, Rich Caruana
KDD 2022 | July 2022
Differentially Private Estimation of Heterogeneous Causal Effects
Fengshi Niu, Harsha Nori, Brian Quistorff, Rich Caruana, Donald Ngwe, Aadharsh Kannan
CLeaR 2022 | April 2022
Node-GAM: Neural Generalized Additive Model For Interpretable Deep Learning
Chun-Hao Chang, Rich Caruana, Anna Goldenberg
ICLR 2022 | April 2022
GAM Changer: Editing Generalized Additive Models with Interactive Visualization
Zijie J. Wang, Alex Kale, Harsha Nori, Peter Stella, Mark Nunnally, Duen Horng Chau, Mihaela Vorvoreanu, Jennifer Wortman Vaughan, Rich Caruana
2021 Neural Information Processing Systems | December 2021
Summarize with Caution: Comparing Global Feature Attributions
Alex Okeson, Rich Caruana, Nick Craswell, Kori Inkpen, Scott M. Lundberg, Harsha Nori, Hanna Wallach, Jennifer Wortman Vaughan
Bulletin of the IEEE Computer Society Technical Committee on Data Engineering | December 2021
Neural Additive Models: Interpretable Machine Learning with Neural Nets
Rishabh Agarwal, Levi Melnick, Xuezhou Zhang, Ben Lengerich, Rich Caruana, Geoffrey Hinton
NeurIPS 2021 | December 2021
Extracting Clinician’s Goals by What-if Interpretable Modeling
Chun-Hao Chang, George Alexandru Adam, Rich Caruana, Anna Goldenberg
AISTATS 2022 | October 2021
In review
Dropout as a Regularizer of Interaction Effects
Benjamin Lengerich, Eric P. Xing, Rich Caruana
October 2021
How Interpretable and Trustworthy are GAMs
Chun-Hao Chang, Sarah Tan, Ben Lengerich, Anna Goldenberg, Rich Caruana
KDD 2021 | August 2021
Accuracy, Interpretability, and Differential Privacy via Explainable Boosting
Harsha Nori, Rich Caruana, Zhiqi Bu, Judy Hanwen Shen, Janardhan (Jana) Kulkarni
2021 International Conference on Machine Learning | July 2021
Purifying Interaction Effects with the Functional ANOVA: An Efficient Algorithm for Recovering Identifiable Additive Models
Benjamin Lengerich, Sarah Tan, Chun-Hao Chang, Giles Hooker, Rich Caruana
International Conference on Artificial Intelligence and Statistics (AISTATS) 2020 | August 2020
Interpreting Interpretability: Understanding Data Scientists’ Use of Interpretability Tools for Machine Learning
Harmanpreet Kaur, Harsha Nori, Samuel Jenkins, Rich Caruana, Hanna Wallach, Jennifer Wortman Vaughan
CHI 2020 | April 2020
CHI 2020 Honorable Mention Award
Efficient Forward Architecture Search
Hanzhang Hu, John Langford, Rich Caruana, Saurajit Mukherjee, Eric Horvitz, Debadeepta Dey
Thirty-third Conference on Neural Information Processing Systems (NeurIPS 2019) | December 2019
InterpretML: A Unified Framework for Machine Learning Interpretability
Harsha Nori, Samuel Jenkins, Paul Koch, Rich Caruana
September 2019
Axiomatic Interpretability for Multiclass Additive Models
Xuezhou Zhang, Sarah Tan, Paul Koch, Yin Lou, Urszula Chajewska, Rich Caruana
The 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD ’19) | August 2019
Gamut: A Design Probe to Understand How Data Scientists Understand Machine Learning Models
Fred Hohman, Andrew Head, Rich Caruana, Robert DeLIne, Steven Drucker
SIGCHI | May 2019
Identifying Unknown Unknowns in the Open World: Representations and Policies for Guided Exploration
Himabindu Lakkaraju, Ece Kamar, Rich Caruana, Eric Horvitz
Thirty-First AAAI Conference on Artificial Intelligence | December 2016
Improving Document Ranking with Dual Word Embeddings
Eric Nalisnick, Bhaskar Mitra, Nick Craswell, Rich Caruana
WWW'16 | April 2016
A Dual Embedding Space Model for Document Ranking
Bhaskar Mitra, Eric Nalisnick, Nick Craswell, Rich Caruana
February 2016
This paper is an extended evaluation and analysis of the model proposed in a poster to appear in WWW'16, April 11 - 15, 2016, Montreal, Canada.
Intelligible Models for HealthCare: Predicting Pneumonia Risk and Hospital 30-day Readmission
Rich Caruana, Paul Koch, Yin Lou, Marc Sturm , Johannes Gehrke, Noemie Elhadad
KDD'15, August 10-13, 2015, Sydney, NSW, Australia | August 2015
ISBN: 978-1-4503-3664-2/15/08
Active Learning with Model Selection
Alnur Ali, Rich Caruana, Ashish Kapoor
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence | July 2014
Gauss Meets Canadian Traveler: Shortest-Path Problems with Correlated Natural Dynamics
Debadeepta Dey, Andrey Kolobov, Rich Caruana, Ece Kamar, Eric Horvitz, Ashish Kapoor
AAMAS 2014 | May 2014
Structured Labeling for Facilitating Concept Evolution in Machine Learning
Todd Kulesza, Saleema Amershi, Rich Caruana, Danyel Fisher, Denis Charles
Proceedings of the Conference on Human Factors in Computing Systems (CHI 2014) | May 2014
Best Paper Award
Accurate Intelligible Models with Pairwise Interactions
Yin Lou , Rich Caruana, Giles Hooker , Johannes Gehrke
KDD'13, August 11-14, 2013, Chicago, Illinois, USA | August 2013
ISBN: 978-1-4503-2174-7/13/08
Learning Speaker, Addressee and Overlap Detection Models from Multimodal Streams
Oriol Vinyals, Dan Bohus, Rich Caruana
ICMI '12 Proceedings of the 14th ACM International Conference on Multimodal Interaction | October 2012
Intelligible Models for Classiï¬cation and Regression
Yin Lou, Rich Caruana, Johannes Gehrke
KDD'12, Beijing, China | August 2012
ISBN: 978-1-4503-1462-6
-
Missing Values and Imputation in Healthcare Data: Can Interpretable Machine Learning Help?
Zhi Chen, Sarah Tan, Urszula Chajewska, Cynthia Rudin , Rich Caruana
Conference on Health, Inference, and Learning (CHIL) 2023 | June 2023
Automated Interpretable Discovery of Heterogeneous Treatment Effectiveness: A Covid-19 Case Study
Benjamin J. Lengerich, Mark E. Nunally, Yin Aphinyanaphongs, Rich Caruana
November 2021
Extracting Clinician’s Goals by What-if Interpretable Modeling
Chun-Hao Chang, George Alexandru Adam, Rich Caruana, Anna Goldenberg
AISTATS 2022 | October 2021
In review
-
GAM Coach: Towards Interactive and User-Centered Algorithmic Recourse
Zijie J. Wang, Jennifer Wortman Vaughan, Rich Caruana, Duen Horng Chau
2023 ACM CHI Conference on Human Factors in Computing Systems (CHI 2023) | February 2023
GAM Changer: Editing Generalized Additive Models with Interactive Visualization
Zijie J. Wang, Alex Kale, Harsha Nori, Peter Stella, Mark Nunnally, Duen Horng Chau, Mihaela Vorvoreanu, Jennifer Wortman Vaughan, Rich Caruana
2021 Neural Information Processing Systems | December 2021
Interpreting Interpretability: Understanding Data Scientists’ Use of Interpretability Tools for Machine Learning
Harmanpreet Kaur, Harsha Nori, Samuel Jenkins, Rich Caruana, Hanna Wallach, Jennifer Wortman Vaughan
CHI 2020 | April 2020
CHI 2020 Honorable Mention Award
Gamut: A Design Probe to Understand How Data Scientists Understand Machine Learning Models
Fred Hohman, Andrew Head, Rich Caruana, Robert DeLIne, Steven Drucker
SIGCHI | May 2019
Structured Labeling for Facilitating Concept Evolution in Machine Learning
Todd Kulesza, Saleema Amershi, Rich Caruana, Danyel Fisher, Denis Charles
Proceedings of the Conference on Human Factors in Computing Systems (CHI 2014) | May 2014
Best Paper Award
Learning Speaker, Addressee and Overlap Detection Models from Multimodal Streams
Oriol Vinyals, Dan Bohus, Rich Caruana
ICMI '12 Proceedings of the 14th ACM International Conference on Multimodal Interaction | October 2012
-
Differentially Private Estimation of Heterogeneous Causal Effects
Fengshi Niu, Harsha Nori, Brian Quistorff, Rich Caruana, Donald Ngwe, Aadharsh Kannan
CLeaR 2022 | April 2022
-
Differentially Private Estimation of Heterogeneous Causal Effects
Fengshi Niu, Harsha Nori, Brian Quistorff, Rich Caruana, Donald Ngwe, Aadharsh Kannan
CLeaR 2022 | April 2022
-
Purifying Interaction Effects with the Functional ANOVA: An Efficient Algorithm for Recovering Identifiable Additive Models
Benjamin Lengerich, Sarah Tan, Chun-Hao Chang, Giles Hooker, Rich Caruana
International Conference on Artificial Intelligence and Statistics (AISTATS) 2020 | August 2020
Implicit Preference Labels for Learning Highly Selective Personalized Rankers
Paul N. Bennett, Milad Shokouhi, Rich Caruana
Proceedings of the 1st ACM SIGIR International Conference on the Theory of Information Retrieval (ICTIR 2015) | September 2015
-
Efficient Forward Architecture Search
Hanzhang Hu, John Langford, Rich Caruana, Saurajit Mukherjee, Eric Horvitz, Debadeepta Dey
Thirty-third Conference on Neural Information Processing Systems (NeurIPS 2019) | December 2019
Improving Document Ranking with Dual Word Embeddings
Eric Nalisnick, Bhaskar Mitra, Nick Craswell, Rich Caruana
WWW'16 | April 2016
A Dual Embedding Space Model for Document Ranking
Bhaskar Mitra, Eric Nalisnick, Nick Craswell, Rich Caruana
February 2016
This paper is an extended evaluation and analysis of the model proposed in a poster to appear in WWW'16, April 11 - 15, 2016, Montreal, Canada.
Implicit Preference Labels for Learning Highly Selective Personalized Rankers
Paul N. Bennett, Milad Shokouhi, Rich Caruana
Proceedings of the 1st ACM SIGIR International Conference on the Theory of Information Retrieval (ICTIR 2015) | September 2015
-
Gamut: A Design Probe to Understand How Data Scientists Understand Machine Learning Models
Fred Hohman, Andrew Head, Rich Caruana, Robert DeLIne, Steven Drucker
SIGCHI | May 2019
Learning Likely Locations
John Krumm, Rich Caruana, Scott Counts
January 2011
-
Gauss Meets Canadian Traveler: Shortest-Path Problems with Correlated Natural Dynamics
Debadeepta Dey, Andrey Kolobov, Rich Caruana, Ece Kamar, Eric Horvitz, Ashish Kapoor
AAMAS 2014 | May 2014
Publications by Type
-
Missing Values and Imputation in Healthcare Data: Can Interpretable Machine Learning Help?
Zhi Chen, Sarah Tan, Urszula Chajewska, Cynthia Rudin , Rich Caruana
Conference on Health, Inference, and Learning (CHIL) 2023 | June 2023
GAM Coach: Towards Interactive and User-Centered Algorithmic Recourse
Zijie J. Wang, Jennifer Wortman Vaughan, Rich Caruana, Duen Horng Chau
2023 ACM CHI Conference on Human Factors in Computing Systems (CHI 2023) | February 2023
Interpretability, Then What? Editing Machine Learning Models to Reflect Human Knowledge and Values
Zijie J. Wang, Alex Kale, Harsha Nori, Peter Stella, Mark E. Nunnally, Duen Horng Chau, Mihaela Vorvoreanu, Jennifer Wortman Vaughan, Rich Caruana
KDD 2022 | July 2022
Differentially Private Estimation of Heterogeneous Causal Effects
Fengshi Niu, Harsha Nori, Brian Quistorff, Rich Caruana, Donald Ngwe, Aadharsh Kannan
CLeaR 2022 | April 2022
Node-GAM: Neural Generalized Additive Model For Interpretable Deep Learning
Chun-Hao Chang, Rich Caruana, Anna Goldenberg
ICLR 2022 | April 2022
GAM Changer: Editing Generalized Additive Models with Interactive Visualization
Zijie J. Wang, Alex Kale, Harsha Nori, Peter Stella, Mark Nunnally, Duen Horng Chau, Mihaela Vorvoreanu, Jennifer Wortman Vaughan, Rich Caruana
2021 Neural Information Processing Systems | December 2021
Neural Additive Models: Interpretable Machine Learning with Neural Nets
Rishabh Agarwal, Levi Melnick, Xuezhou Zhang, Ben Lengerich, Rich Caruana, Geoffrey Hinton
NeurIPS 2021 | December 2021
Extracting Clinician’s Goals by What-if Interpretable Modeling
Chun-Hao Chang, George Alexandru Adam, Rich Caruana, Anna Goldenberg
AISTATS 2022 | October 2021
In review
How Interpretable and Trustworthy are GAMs
Chun-Hao Chang, Sarah Tan, Ben Lengerich, Anna Goldenberg, Rich Caruana
KDD 2021 | August 2021
Accuracy, Interpretability, and Differential Privacy via Explainable Boosting
Harsha Nori, Rich Caruana, Zhiqi Bu, Judy Hanwen Shen, Janardhan (Jana) Kulkarni
2021 International Conference on Machine Learning | July 2021
Purifying Interaction Effects with the Functional ANOVA: An Efficient Algorithm for Recovering Identifiable Additive Models
Benjamin Lengerich, Sarah Tan, Chun-Hao Chang, Giles Hooker, Rich Caruana
International Conference on Artificial Intelligence and Statistics (AISTATS) 2020 | August 2020
Interpreting Interpretability: Understanding Data Scientists’ Use of Interpretability Tools for Machine Learning
Harmanpreet Kaur, Harsha Nori, Samuel Jenkins, Rich Caruana, Hanna Wallach, Jennifer Wortman Vaughan
CHI 2020 | April 2020
CHI 2020 Honorable Mention Award
Efficient Forward Architecture Search
Hanzhang Hu, John Langford, Rich Caruana, Saurajit Mukherjee, Eric Horvitz, Debadeepta Dey
Thirty-third Conference on Neural Information Processing Systems (NeurIPS 2019) | December 2019
Axiomatic Interpretability for Multiclass Additive Models
Xuezhou Zhang, Sarah Tan, Paul Koch, Yin Lou, Urszula Chajewska, Rich Caruana
The 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD ’19) | August 2019
Gamut: A Design Probe to Understand How Data Scientists Understand Machine Learning Models
Fred Hohman, Andrew Head, Rich Caruana, Robert DeLIne, Steven Drucker
SIGCHI | May 2019
Identifying Unknown Unknowns in the Open World: Representations and Policies for Guided Exploration
Himabindu Lakkaraju, Ece Kamar, Rich Caruana, Eric Horvitz
Thirty-First AAAI Conference on Artificial Intelligence | December 2016
Improving Document Ranking with Dual Word Embeddings
Eric Nalisnick, Bhaskar Mitra, Nick Craswell, Rich Caruana
WWW'16 | April 2016
Implicit Preference Labels for Learning Highly Selective Personalized Rankers
Paul N. Bennett, Milad Shokouhi, Rich Caruana
Proceedings of the 1st ACM SIGIR International Conference on the Theory of Information Retrieval (ICTIR 2015) | September 2015
Intelligible Models for HealthCare: Predicting Pneumonia Risk and Hospital 30-day Readmission
Rich Caruana, Paul Koch, Yin Lou, Marc Sturm , Johannes Gehrke, Noemie Elhadad
KDD'15, August 10-13, 2015, Sydney, NSW, Australia | August 2015
ISBN: 978-1-4503-3664-2/15/08
Active Learning with Model Selection
Alnur Ali, Rich Caruana, Ashish Kapoor
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence | July 2014
Gauss Meets Canadian Traveler: Shortest-Path Problems with Correlated Natural Dynamics
Debadeepta Dey, Andrey Kolobov, Rich Caruana, Ece Kamar, Eric Horvitz, Ashish Kapoor
AAMAS 2014 | May 2014
Structured Labeling for Facilitating Concept Evolution in Machine Learning
Todd Kulesza, Saleema Amershi, Rich Caruana, Danyel Fisher, Denis Charles
Proceedings of the Conference on Human Factors in Computing Systems (CHI 2014) | May 2014
Best Paper Award
Accurate Intelligible Models with Pairwise Interactions
Yin Lou , Rich Caruana, Giles Hooker , Johannes Gehrke
KDD'13, August 11-14, 2013, Chicago, Illinois, USA | August 2013
ISBN: 978-1-4503-2174-7/13/08
Learning Speaker, Addressee and Overlap Detection Models from Multimodal Streams
Oriol Vinyals, Dan Bohus, Rich Caruana
ICMI '12 Proceedings of the 14th ACM International Conference on Multimodal Interaction | October 2012
Intelligible Models for Classiï¬cation and Regression
Yin Lou, Rich Caruana, Johannes Gehrke
KDD'12, Beijing, China | August 2012
ISBN: 978-1-4503-1462-6
Learning Likely Locations
John Krumm, Rich Caruana, Scott Counts
January 2011
-
Summarize with Caution: Comparing Global Feature Attributions
Alex Okeson, Rich Caruana, Nick Craswell, Kori Inkpen, Scott M. Lundberg, Harsha Nori, Hanna Wallach, Jennifer Wortman Vaughan
Bulletin of the IEEE Computer Society Technical Committee on Data Engineering | December 2021
-
Automated Interpretable Discovery of Heterogeneous Treatment Effectiveness: A Covid-19 Case Study
Benjamin J. Lengerich, Mark E. Nunally, Yin Aphinyanaphongs, Rich Caruana
November 2021
Dropout as a Regularizer of Interaction Effects
Benjamin Lengerich, Eric P. Xing, Rich Caruana
October 2021
InterpretML: A Unified Framework for Machine Learning Interpretability
Harsha Nori, Samuel Jenkins, Paul Koch, Rich Caruana
September 2019
A Dual Embedding Space Model for Document Ranking
Bhaskar Mitra, Eric Nalisnick, Nick Craswell, Rich Caruana
February 2016
This paper is an extended evaluation and analysis of the model proposed in a poster to appear in WWW'16, April 11 - 15, 2016, Montreal, Canada.