Cynthia Rudin

ORCID

Publication Activity (10 Years)

Years Active: 2003-2024
Publications (10 Years): 168

Top Venues

Publications

Harsh Parikh, Quinn Lanners, Zade Akras, Sahar Zafar, M. Brandon Westover, Cynthia Rudin, Alexander Volfovsky
Safe and Interpretable Estimation of Optimal Treatment Regimes. AISTATS (2024)
Elita A. Lobo, Harvineet Singh, Marek Petrik, Cynthia Rudin, Himabindu Lakkaraju
Data Poisoning Attacks on Off-Policy Policy Evaluation Methods. CoRR (2024)
Travis Seale-Carlisle, Saksham Jain, Courtney Lee, Caroline Levenson, Swathi Ramprasad, Brandon Garrett, Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky
Evaluating Pre-trial Programs Using Interpretable Machine Learning Matching Algorithms for Causal Inference. AAAI (2024)
Yiyang Sun, Zhi Chen, Vittorio Orlandi, Tong Wang, Cynthia Rudin
Sparse and Faithful Explanations Without Sparse Models. AISTATS (2024)
Yiyang Sun, Zhi Chen, Vittorio Orlandi, Tong Wang, Cynthia Rudin
Sparse and Faithful Explanations Without Sparse Models. CoRR (2024)
Srikar Katta, Harsh Parikh, Cynthia Rudin, Alexander Volfovsky
Interpretable Causal Inference for Analyzing Wearable, Sensor, and Distributional Data. AISTATS (2024)
Rui Zhang, Rui Xin, Margo I. Seltzer, Cynthia Rudin
Optimal Sparse Survival Trees. CoRR (2024)
Cheng Ding, Zhicheng Guo, Cynthia Rudin, Ran Xiao, Amit J. Shah, Duc H. Do, Randall J. Lee, Gari D. Clifford, Fadi B. Nahab, Xiao Hu
Learning From Alarms: A Robust Learning Approach for Accurate Photoplethysmography-Based Atrial Fibrillation Detection Using Eight Million Samples Labeled With Imprecise Arrhythmia Alarms. IEEE J. Biomed. Health Informatics 28 (5) (2024)
Rui Zhang, Rui Xin, Margo I. Seltzer, Cynthia Rudin
Optimal Sparse Survival Trees. AISTATS (2024)
Cynthia Rudin, Chudi Zhong, Lesia Semenova, Margo I. Seltzer, Ronald Parr, Jiachang Liu, Srikar Katta, Jon Donnelly, Harry Chen, Zachery Boner
Amazing Things Come From Having Many Good Models. CoRR (2024)
Cheng Ding, Zhicheng Guo, Zhaoliang Chen, Randall J. Lee, Cynthia Rudin, Xiao Hu
SiamQuality: A ConvNet-Based Foundation Model for Imperfect Physiological Signals. CoRR (2024)
Julia Yang, Alina Jade Barnett, Jon Donnelly, Satvik Kishore, Jerry Fang, Fides Regina Schwartz, Chaofan Chen, Joseph Y. Lo, Cynthia Rudin
FPN-IAIA-BL: A Multi-Scale Interpretable Deep Learning Model for Classification of Mass Margins in Digital Mammography. CoRR (2024)
Manickam Ashokkumar, Wenwen Mei, Jackson J. Peterson, Yuriko Harigaya, David M. Murdoch, David M. Margolis, Caleb Kornfein, Alexander X. Oesterling, Zhicheng Guo, Cynthia Rudin, Yuchao Jiang, Edward P. Browne
Integrated Single-cell Multiomic Analysis of HIV Latency Reversal Reveals Novel Regulators of Viral Reactivation. Genom. Proteom. Bioinform. 22 (1) (2024)
Stephen Hahn, Jerry Yin, Rico Zhu, Weihan Xu, Yue Jiang, Simon Mak, Cynthia Rudin
SentHYMNent: An Interpretable and Sentiment-Driven Model for Algorithmic Melody Harmonization. KDD (2024)
Varun Babbar, Zhicheng Guo, Cynthia Rudin
What is different between these datasets? CoRR (2024)
Frank Willard, Luke Moffett, Emmanuel Mokel, Jon Donnelly, Stark Guo, Julia Yang, Giyoung Kim, Alina Jade Barnett, Cynthia Rudin
This Looks Better than That: Better Interpretable Models with ProtoPNeXt. CoRR (2024)
Chiyu Ma, Brandon Zhao, Chaofan Chen, Cynthia Rudin
This Looks Like Those: Illuminating Prototypical Concepts Using Multiple Visualizations. NeurIPS (2023)
Lina Zhou, Cynthia Rudin, Matthew Gombolay, Jim Spohrer, Michelle Zhou, Souren Paul
From Artificial Intelligence (AI) to Intelligence Augmentation (IA): Design Principles, Potential Risks, and Emerging Issues. AIS Trans. Hum. Comput. Interact. 15 (1) (2023)
Jiachang Liu, Sam Rosen, Chudi Zhong, Cynthia Rudin
OKRidge: Scalable Optimal k-Sparse Ridge Regression for Learning Dynamical Systems. CoRR (2023)
Quinn Lanners, Harsh Parikh, Alexander Volfovsky, Cynthia Rudin, David Page
From Feature Importance to Distance Metric: An Almost Exact Matching Approach for Causal Inference. CoRR (2023)
Rui Zhang, Rui Xin, Margo I. Seltzer, Cynthia Rudin
Optimal Sparse Regression Trees. AAAI (2023)
Cheng Ding, Zhicheng Guo, Cynthia Rudin, Ran Xiao, Fadi B. Nahab, Xiao Hu
Reconsideration on evaluation of machine learning models in continuous monitoring using wearables. CoRR (2023)
Jiachang Liu, Sam Rosen, Chudi Zhong, Cynthia Rudin
OKRidge: Scalable Optimal k-Sparse Ridge Regression. NeurIPS (2023)
Harsh Parikh, Quinn Lanners, Zade Akras, Sahar F. Zafar, M. Brandon Westover, Cynthia Rudin, Alexander Volfovsky
Estimating Trustworthy and Safe Optimal Treatment Regimes. CoRR (2023)
Lesia Semenova, Harry Chen, Ronald Parr, Cynthia Rudin
A Path to Simpler Models Starts With Noise. CoRR (2023)
Edwin Agnew, Michelle Qiu, Lily Zhu, Sam Wiseman, Cynthia Rudin
The Mechanical Bard: An Interpretable Machine Learning Approach to Shakespearean Sonnet Generation. ACL (2) (2023)
Marco Morucci, Vittorio Orlandi, Harsh Parikh, Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky
A Double Machine Learning Approach to Combining Experimental and Observational Data. CoRR (2023)
Chudi Zhong, Zhi Chen, Jiachang Liu, Margo I. Seltzer, Cynthia Rudin
Exploring and Interacting with the Set of Good Sparse Generalized Additive Models. NeurIPS (2023)
Quinn Lanners, Harsh Parikh, Alexander Volfovsky, Cynthia Rudin, David Page
Variable importance matching for causal inference. UAI (2023)
Han Zhang, Rayehe Karimi Mahabadi, Cynthia Rudin, Johann Guilleminot, L. Catherine Brinson
Uncertainty Quantification of Bandgaps in Acoustic Metamaterials with Stochastic Geometric Defects and Material Properties. CoRR (2023)
Yanchen Ou, Alina Jade Barnett, Anika Mitra, Fides Regina Schwartz, Chaofan Chen, Lars J. Grimm, Joseph Y. Lo, Cynthia Rudin
A user interface to communicate interpretable AI decisions to radiologists (Erratum). Medical Imaging: Image Perception, Observer Performance, and Technology Assessment (2023)
Zhicheng Guo, Cheng Ding, Duc H. Do, Amit Shah, Randall J. Lee, Xiao Hu, Cynthia Rudin
SiamAF: Learning Shared Information from ECG and PPG Signals for Robust Atrial Fibrillation Detection. CoRR (2023)
Lesia Semenova, Harry Chen, Ronald Parr, Cynthia Rudin
A Path to Simpler Models Starts With Noise. NeurIPS (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)
Jon Donnelly, Srikar Katta, Cynthia Rudin, Edward P. Browne
The Rashomon Importance Distribution: Getting RID of Unstable, Single Model-based Variable Importance. CoRR (2023)
Srikar Katta, Harsh Parikh, Cynthia Rudin, Alexander Volfovsky
Interpretable Causal Inference for Analyzing Wearable, Sensor, and Distributional Data. CoRR (2023)
Chloe Qinyu Zhu, Muhang Tian, Lesia Semenova, Jiachang Liu, Jack Xu, Joseph Scarpa, Cynthia Rudin
Fast and Interpretable Mortality Risk Scores for Critical Care Patients. CoRR (2023)
Chiyu Ma, Brandon Zhao, Chaofan Chen, Cynthia Rudin
This Looks Like Those: Illuminating Prototypical Concepts Using Multiple Visualizations. CoRR (2023)
Sully F. Chen, Zhicheng Guo, Cheng Ding, Xiao Hu, Cynthia Rudin
Learned Kernels for Interpretable and Efficient PPG Signal Quality Assessment and Artifact Segmentation. CoRR (2023)
Dennis Tang, Frank Willard, Ronan Tegerdine, Luke Triplett, Jon Donnelly, Luke Moffett, Lesia Semenova, Alina Jade Barnett, Jin Jing, Cynthia Rudin, M. Brandon Westover
ProtoEEGNet: An Interpretable Approach for Detecting Interictal Epileptiform Discharges. CoRR (2023)
Cynthia Rudin, Yaron Shaposhnik
Globally-Consistent Rule-Based Summary-Explanations for Machine Learning Models: Application to Credit-Risk Evaluation. J. Mach. Learn. Res. 24 (2023)
Stephen Hahn, Rico Zhu, Simon Mak, Cynthia Rudin, Yue Jiang
An Interpretable, Flexible, and Interactive Probabilistic Framework for Melody Generation. KDD (2023)
Zhi Chen, Chudi Zhong, Margo I. Seltzer, Cynthia Rudin
Understanding and Exploring the Whole Set of Good Sparse Generalized Additive Models. CoRR (2023)
Yanchen Jessie Ou, Alina Jade Barnett, Anika Mitra, Fides Regina Schwartz, Chaofan Chen, Lars J. Grimm, Joseph Y. Lo, Cynthia Rudin
A user interface to communicate interpretable AI decisions to radiologists. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment (2023)
Pranay Jain, Cheng Ding, Cynthia Rudin, Xiao Hu
A Self-Supervised Algorithm for Denoising Photoplethysmography Signals for Heart Rate Estimation from Wearables. CoRR (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)
Jon Donnelly, Srikar Katta, Cynthia Rudin, Edward P. Browne
The Rashomon Importance Distribution: Getting RID of Unstable, Single Model-based Variable Importance. NeurIPS (2023)
Chaofan Chen, Kangcheng Lin, Cynthia Rudin, Yaron Shaposhnik, Sijia Wang, Tong Wang
A holistic approach to interpretability in financial lending: Models, visualizations, and summary-explanations. Decis. Support Syst. 152 (2022)
Jiachang Liu, Chudi Zhong, Boxuan Li, Margo I. Seltzer, Cynthia Rudin
FasterRisk: Fast and Accurate Interpretable Risk Scores. NeurIPS (2022)
Ali Behrouz, Mathias Lécuyer, Cynthia Rudin, Mango I. Seltzer
Fast optimization of weighted sparse decision trees for use in optimal treatment regimes and optimal policy design. CIKM Workshops (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
Why Interpretable Causal Inference is Important for High-Stakes Decision Making for Critically Ill Patients and How To Do It. CoRR (2022)
Elita A. Lobo, Harvineet Singh, Marek Petrik, Cynthia Rudin, Himabindu Lakkaraju
Data poisoning attacks on off-policy policy evaluation methods. UAI (2022)
Lesia Semenova, Cynthia Rudin, Ronald Parr
On the Existence of Simpler Machine Learning Models. FAccT (2022)
Haiyang Huang, Zhi Chen, Cynthia Rudin
SegDiscover: Visual Concept Discovery via Unsupervised Semantic Segmentation. CoRR (2022)
Zijie J. Wang, Chudi Zhong, Rui Xin, Takuya Takagi, Zhi Chen, Duen Horng Chau, Cynthia Rudin, Margo I. Seltzer
TimberTrek: Exploring and Curating Sparse Decision Trees with Interactive Visualization. IEEE VIS (Short Papers) (2022)
Rui Xin, Chudi Zhong, Zhi Chen, Takuya Takagi, Margo I. Seltzer, Cynthia Rudin
Exploring the Whole Rashomon Set of Sparse Decision Trees. CoRR (2022)
Jiachang Liu, Chudi Zhong, Margo I. Seltzer, Cynthia Rudin
Fast Sparse Classification for Generalized Linear and Additive Models. CoRR (2022)
Harsh Parikh, Cynthia Rudin, Alexander Volfovsky
MALTS: Matching After Learning to Stretch. J. Mach. Learn. Res. 23 (2022)
Rui Xin, Chudi Zhong, Zhi Chen, Takuya Takagi, Margo I. Seltzer, Cynthia Rudin
Exploring the Whole Rashomon Set of Sparse Decision Trees. NeurIPS (2022)
Ali Behrouz, Mathias Lécuyer, Cynthia Rudin, Margo I. Seltzer
Fast Optimization of Weighted Sparse Decision Trees for use in Optimal Treatment Regimes and Optimal Policy Design. CoRR (2022)
Tong Wang, Cynthia Rudin
Causal Rule Sets for Identifying Subgroups with Enhanced Treatment Effects. INFORMS J. Comput. 34 (3) (2022)
Yishay Mansour, Michal Moshkovitz, Cynthia Rudin
There is no Accuracy-Interpretability Tradeoff in Reinforcement Learning for Mazes. CoRR (2022)
Jiachang Liu, Chudi Zhong, Margo I. Seltzer, Cynthia Rudin
Fast Sparse Classification for Generalized Linear and Additive Models. AISTATS (2022)
Hayden McTavish, Chudi Zhong, Reto Achermann, Ilias Karimalis, Jacques Chen, Cynthia Rudin, Margo I. Seltzer
Fast Sparse Decision Tree Optimization via Reference Ensembles. AAAI (2022)
Rui Zhang, Rui Xin, Margo I. Seltzer, Cynthia Rudin
Optimal Sparse Regression Trees. CoRR (2022)
Alina Jade Barnett, Vaibhav Sharma, Neel Gajjar, Jerry Fang, Fides Regina Schwartz, Chaofan Chen, Joseph Y. Lo, Cynthia Rudin
Interpretable deep learning models for better clinician-AI communication in clinical mammography. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment (2022)
Chunxiao Li, Cynthia Rudin, Tyler H. McCormick
Rethinking Nonlinear Instrumental Variable Models through Prediction Validity. J. Mach. Learn. Res. 23 (2022)
Zijie J. Wang, Chudi Zhong, Rui Xin, Takuya Takagi, Zhi Chen, Duen Horng Chau, Cynthia Rudin, Margo I. Seltzer
TimberTrek: Exploring and Curating Sparse Decision Trees with Interactive Visualization. CoRR (2022)
Alina Jade Barnett, Zhicheng Guo, Jin Jing, Wendong Ge, Cynthia Rudin, M. Brandon Westover
Mapping the Ictal-Interictal-Injury Continuum Using Interpretable Machine Learning. CoRR (2022)
Jiachang Liu, Chudi Zhong, Boxuan Li, Margo I. Seltzer, Cynthia Rudin
FasterRisk: Fast and Accurate Interpretable Risk Scores. CoRR (2022)
Yingfan Wang, Haiyang Huang, Cynthia Rudin, Yaron Shaposhnik
Understanding How Dimension Reduction Tools Work: An Empirical Approach to Deciphering t-SNE, UMAP, TriMap, and PaCMAP for Data Visualization. J. Mach. Learn. Res. 22 (2021)
Zhi Chen, Alexander C. Ogren, Chiara Daraio, L. Catherine Brinson, Cynthia Rudin
How to See Hidden Patterns in Metamaterials with Interpretable Machine Learning. CoRR (2021)
Jianyou Wang, Cynthia Rudin, Yuren Zhou, Christopher Suh, Xiaoxuan Zhang
There Once Was a Really Bad Poet, It Was Automated but You Didn't Know It. Trans. Assoc. Comput. Linguistics 9 (2021)
Tianyu Wang, Marco Morucci, M. Usaid Awan, Yameng Liu, Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky
FLAME: A Fast Large-scale Almost Matching Exactly Approach to Causal Inference. J. Mach. Learn. Res. 22 (2021)
Divya Koyyalagunta, Anna Sun, Rachel Lea Draelos, Cynthia Rudin
Playing Codenames with Language Graphs and Word Embeddings. CoRR (2021)
Hayden McTavish, Chudi Zhong, Reto Achermann, Ilias Karimalis, Jacques Chen, Cynthia Rudin, Margo I. Seltzer
Fast Sparse Decision Tree Optimization via Reference Ensembles. CoRR (2021)
Chaofan Chen, Kangcheng Lin, Cynthia Rudin, Yaron Shaposhnik, Sijia Wang, Tong Wang
A Holistic Approach to Interpretability in Financial Lending: Models, Visualizations, and Summary-Explanations. CoRR (2021)
Yunyao Zhu, Stephen Hahn, Simon Mak, Yue Jiang, Cynthia Rudin
BacHMMachine: An Interpretable and Scalable Model for Algorithmic Harmonization for Four-part Baroque Chorales. CoRR (2021)
Alex Oesterling, Angikar Ghosal, Haoyang Yu, Rui Xin, Yasa Baig, Lesia Semenova, Cynthia Rudin
Multitask Learning for Citation Purpose Classification. CoRR (2021)
Beau Coker, Cynthia Rudin, Gary King
A Theory of Statistical Inference for Ensuring the Robustness of Scientific Results. Manag. Sci. 67 (10) (2021)
Alina Jade Barnett, Fides Regina Schwartz, Chaofan Tao, Chaofan Chen, Yinhao Ren, Joseph Y. Lo, Cynthia Rudin
Interpretable Mammographic Image Classification using Cased-Based Reasoning and Deep Learning. CoRR (2021)
Stefano Tracà, Cynthia Rudin, Weiyu Yan
Regulating Greed Over Time in Multi-Armed Bandits. J. Mach. Learn. Res. 22 (2021)
Michael Anis Mihdi Afnan, Cynthia Rudin, Vincent Conitzer, Julian Savulescu, Abhishek Mishra, Yanhe Liu, Masoud Afnan
Ethical Implementation of Artificial Intelligence to Select Embryos in In Vitro Fertilization. CoRR (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
dame-flame: A Python Library Providing Fast Interpretable Matching for Causal Inference. CoRR (2021)
Jianyou Wang, Xiaoxuan Zhang, Yuren Zhou, Christopher Suh, Cynthia Rudin
There Once Was a Really Bad Poet, It Was Automated but You Didn't Know It. CoRR (2021)
Divya Koyyalagunta, Anna Sun, Rachel Lea Draelos, Cynthia Rudin
Playing Codenames with Language Graphs and Word Embeddings. J. Artif. Intell. Res. 71 (2021)
Alina Jade Barnett, Fides Regina Schwartz, Chaofan Tao, Chaofan Chen, Yinhao Ren, Joseph Y. Lo, Cynthia Rudin
A case-based interpretable deep learning model for classification of mass lesions in digital mammography. Nat. Mach. Intell. 3 (12) (2021)
Cynthia Rudin, Chaofan Chen, Zhi Chen, Haiyang Huang, Lesia Semenova, Chudi Zhong
Interpretable Machine Learning: Fundamental Principles and 10 Grand Challenges. CoRR (2021)
Alina Jade Barnett, Fides Regina Schwartz, Chaofan Tao, Chaofan Chen, Yinhao Ren, Joseph Y. Lo, Cynthia Rudin
IAIA-BL: A Case-based Interpretable Deep Learning Model for Classification of Mass Lesions in Digital Mammography. CoRR (2021)
Michael Anis Mihdi Afnan, Cynthia Rudin, Vincent Conitzer, Julian Savulescu, Abhishek Mishra, Yanhe Liu, Masoud Afnan
Ethical Implementation of Artificial Intelligence to Select Embryos in In Vitro Fertilization. AIES (2021)
Yingfan Wang, Haiyang Huang, Cynthia Rudin, Yaron Shaposhnik
Understanding How Dimension Reduction Tools Work: An Empirical Approach to Deciphering t-SNE, UMAP, TriMAP, and PaCMAP for Data Visualization. CoRR (2020)
Jimmy Lin, Chudi Zhong, Diane Hu, Cynthia Rudin, Margo I. Seltzer
Generalized Optimal Sparse Decision Trees. CoRR (2020)
Jimmy Lin, Chudi Zhong, Diane Hu, Cynthia Rudin, Margo I. Seltzer
Generalized and Scalable Optimal Sparse Decision Trees. ICML (2020)
Caroline Wang, Bin Han, Bhrij Patel, Feroze Mohideen, Cynthia Rudin
In Pursuit of Interpretable, Fair and Accurate Machine Learning for Criminal Recidivism Prediction. CoRR (2020)
Tianyu Wang, Cynthia Rudin
Bandits for BMO Functions. ICML (2020)
M. Usaid Awan, Marco Morucci, Vittorio Orlandi, Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky
Almost-Matching-Exactly for Treatment Effect Estimation under Network Interference. CoRR (2020)
Jerry Liu, Nathan O'Hara, Alexander Rubin, Rachel Lea Draelos, Cynthia Rudin
Metaphor Detection Using Contextual Word Embeddings From Transformers. Fig-Lang@ACL (2020)
Marco Morucci, Vittorio Orlandi, Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky
Adaptive Hyper-box Matching for Interpretable Individualized Treatment Effect Estimation. CoRR (2020)
Tianyu Wang, Cynthia Rudin
Bandits for BMO Functions. CoRR (2020)
Marco Morucci, Vittorio Orlandi, Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky
Adaptive Hyper-box Matching for Interpretable Individualized Treatment Effect Estimation. UAI (2020)

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Publication Activity (10 Years)

Top Topics

Top Venues

Cynthia Rudin