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Cynthia Rudin

Duke University

SegDiscover: Visual Concept Discovery via Unsupervised Semantic Segmentation


Apr 22, 2022
Haiyang Huang, Zhi Chen, Cynthia Rudin


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Why Interpretable Causal Inference is Important for High-Stakes Decision Making for Critically Ill Patients and How To Do It


Mar 09, 2022
Harsh Parikh, Kentaro Hoffman, Haoqi Sun, Wendong Ge, Jin Jing, Rajesh Amerineni, Lin Liu, Jimeng Sun, Sahar Zafar, Aaron Struck, Alexander Volfovsky, Cynthia Rudin, M. Brandon Westover


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Fast Sparse Classification for Generalized Linear and Additive Models


Feb 23, 2022
Jiachang Liu, Chudi Zhong, Margo Seltzer, Cynthia Rudin

* To Appear in AISTATS 2022 

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Fast Sparse Decision Tree Optimization via Reference Ensembles


Dec 21, 2021
Hayden McTavish, Chudi Zhong, Reto Achermann, Ilias Karimalis, Jacques Chen, Cynthia Rudin, Margo Seltzer

* Accepted by AAAI 2022 

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How Smart Guessing Strategies Can Yield Massive Scalability Improvements for Sparse Decision Tree Optimization


Dec 01, 2021
Hayden McTavish, Chudi Zhong, Reto Achermann, Ilias Karimalis, Jacques Chen, Cynthia Rudin, Margo Seltzer

* Accepted by AAAI 2022 

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How to See Hidden Patterns in Metamaterials with Interpretable Machine Learning


Nov 10, 2021
Zhi Chen, Alexander Ogren, Chiara Daraio, L. Catherine Brinson, Cynthia Rudin

* Under review 

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BacHMMachine: An Interpretable and Scalable Model for Algorithmic Harmonization for Four-part Baroque Chorales


Sep 15, 2021
Yunyao Zhu, Stephen Hahn, Simon Mak, Yue Jiang, Cynthia Rudin

* 7 pages, 7 figures 

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Interpretable Mammographic Image Classification using Cased-Based Reasoning and Deep Learning


Jul 12, 2021
Alina Jade Barnett, Fides Regina Schwartz, Chaofan Tao, Chaofan Chen, Yinhao Ren, Joseph Y. Lo, Cynthia Rudin

* 10 pages, 6 figures, accepted for oral presentation at the IJCAI-21 Workshop on Deep Learning, Case-Based Reasoning, and AutoML: Present and Future Synergies. arXiv admin note: substantial text overlap with arXiv:2103.12308 

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Multitask Learning for Citation Purpose Classification


Jun 24, 2021
Alex Oesterling, Angikar Ghosal, Haoyang Yu, Rui Xin, Yasa Baig, Lesia Semenova, Cynthia Rudin

* Second Workshop on Scholarly Document Processing 

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A Holistic Approach to Interpretability in Financial Lending: Models, Visualizations, and Summary-Explanations


Jun 04, 2021
Chaofan Chen, Kangcheng Lin, Cynthia Rudin, Yaron Shaposhnik, Sijia Wang, Tong Wang


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Playing Codenames with Language Graphs and Word Embeddings


May 12, 2021
Divya Koyyalagunta, Anna Sun, Rachel Lea Draelos, Cynthia Rudin

* Divya Koyyalagunta and Anna Sun contributed equally to this work. This is an arXiv version of the paper that has been accepted for publication in the Journal of Artificial Intelligence Research (JAIR) 

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Ethical Implementation of Artificial Intelligence to Select Embryos in In Vitro Fertilization


Apr 30, 2021
Michael Anis Mihdi Afnan, Cynthia Rudin, Vincent Conitzer, Julian Savulescu, Abhishek Mishra, Yanhe Liu, Masoud Afnan

* AIES 2021 

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IAIA-BL: A Case-based Interpretable Deep Learning Model for Classification of Mass Lesions in Digital Mammography


Mar 23, 2021
Alina Jade Barnett, Fides Regina Schwartz, Chaofan Tao, Chaofan Chen, Yinhao Ren, Joseph Y. Lo, Cynthia Rudin

* 24 pages, 5 figures, 2 tables 

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Interpretable Machine Learning: Fundamental Principles and 10 Grand Challenges


Mar 20, 2021
Cynthia Rudin, Chaofan Chen, Zhi Chen, Haiyang Huang, Lesia Semenova, Chudi Zhong


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There Once Was a Really Bad Poet, It Was Automated but You Didn't Know It


Mar 05, 2021
Jianyou Wang, Xiaoxuan Zhang, Yuren Zhou, Christopher Suh, Cynthia Rudin

* Paper accepted and will be published at TACL (Transactions of the Association for Computational Linguistics) 2021 

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dame-flame: A Python Library Providing Fast Interpretable Matching for Causal Inference


Jan 14, 2021
Neha R. Gupta, Vittorio Orlandi, Chia-Rui Chang, Tianyu Wang, Marco Morucci, Pritam Dey, Thomas J. Howell, Xian Sun, Angikar Ghosal, Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky

* 5 pages, 1 figure; Reference and discussion of CEM corrected 

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Understanding How Dimension Reduction Tools Work: An Empirical Approach to Deciphering t-SNE, UMAP, TriMAP, and PaCMAP for Data Visualization


Dec 08, 2020
Yingfan Wang, Haiyang Huang, Cynthia Rudin, Yaron Shaposhnik


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Cryo-ZSSR: multiple-image super-resolution based on deep internal learning


Nov 22, 2020
Qinwen Huang, Ye Zhou, Xiaochen Du, Reed Chen, Jianyou Wang, Cynthia Rudin, Alberto Bartesaghi

* 11 pages, 4 figures 

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Generalized and Scalable Optimal Sparse Decision Trees


Jul 17, 2020
Jimmy Lin, Chudi Zhong, Diane Hu, Cynthia Rudin, Margo Seltzer


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Bandits for BMO Functions


Jul 17, 2020
Tianyu Wang, Cynthia Rudin


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Generalized Optimal Sparse Decision Trees


Jun 15, 2020
Jimmy Lin, Chudi Zhong, Diane Hu, Cynthia Rudin, Margo Seltzer


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In Pursuit of Interpretable, Fair and Accurate Machine Learning for Criminal Recidivism Prediction


May 08, 2020
Caroline Wang, Bin Han, Bhrij Patel, Feroze Mohideen, Cynthia Rudin


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PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models


Mar 08, 2020
Sachit Menon, Alexandru Damian, Shijia Hu, Nikhil Ravi, Cynthia Rudin

* Sachit Menon and Alexandru Damian contributed equally. CVPR 2020 camera-ready 

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Adaptive Hyper-box Matching for Interpretable Individualized Treatment Effect Estimation


Mar 03, 2020
Marco Morucci, Vittorio Orlandi, Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky


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Almost-Matching-Exactly for Treatment Effect Estimation under Network Interference


Mar 02, 2020
M. Usaid Awan, Marco Morucci, Vittorio Orlandi, Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky


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Concept Whitening for Interpretable Image Recognition


Feb 05, 2020
Zhi Chen, Yijie Bei, Cynthia Rudin


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A study in Rashomon curves and volumes: A new perspective on generalization and model simplicity in machine learning


Aug 05, 2019
Lesia Semenova, Cynthia Rudin


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Interpretable Almost-Matching-Exactly With Instrumental Variables


Jul 28, 2019
M. Usaid Awan, Yameng Liu, Marco Morucci, Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky

* Proceedings of the Thirty-fifth Conference on Uncertainty in Artificial Intelligence (UAI 2019) 

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Reducing Exploration of Dying Arms in Mortal Bandits


Jul 04, 2019
Stefano Tracà, Cynthia Rudin, Weiyu Yan

* Conference: UAI 2019 

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