Cynthia Rudin
Orcid: 0000-0003-4283-2780Affiliations:
- Duke University, USA
According to our database1,
Cynthia Rudin
authored at least 203 papers
between 2003 and 2024.
Collaborative distances:
Collaborative distances:
Timeline
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Online presence:
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on zbmath.org
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on twitter.com
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on orcid.org
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on id.loc.gov
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on d-nb.info
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Bibliography
2024
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, May, 2024
Sparse learned kernels for interpretable and efficient medical time series processing.
Nat. Mac. Intell., 2024
Integrated Single-cell Multiomic Analysis of HIV Latency Reversal Reveals Novel Regulators of Viral Reactivation.
Genom. Proteom. Bioinform., 2024
Interpretable Image Classification with Adaptive Prototype-based Vision Transformers.
CoRR, 2024
FastSurvival: Hidden Computational Blessings in Training Cox Proportional Hazards Models.
CoRR, 2024
Phononic materials with effectively scale-separated hierarchical features using interpretable machine learning.
CoRR, 2024
A New Dataset, Notation Software, and Representation for Computational Schenkerian Analysis.
CoRR, 2024
CoRR, 2024
SentHYMNent: An Interpretable and Sentiment-Driven Model for Algorithmic Melody Harmonization.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024
Proceedings of the Forty-first International Conference on Machine Learning, 2024
FPN-IAIA-BL: A Multi-Scale Interpretable Deep Learning Model for Classification of Mass Margins in Digital Mammography.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024
Interpretable Causal Inference for Analyzing Wearable, Sensor, and Distributional Data.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024
Evaluating Pre-trial Programs Using Interpretable Machine Learning Matching Algorithms for Causal Inference.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024
2023
From Artificial Intelligence (AI) to Intelligence Augmentation (IA): Design Principles, Potential Risks, and Emerging Issues.
AIS Trans. Hum. Comput. Interact., March, 2023
Globally-Consistent Rule-Based Summary-Explanations for Machine Learning Models: Application to Credit-Risk Evaluation.
J. Mach. Learn. Res., 2023
ProtoEEGNet: An Interpretable Approach for Detecting Interictal Epileptiform Discharges.
CoRR, 2023
Reconsideration on evaluation of machine learning models in continuous monitoring using wearables.
CoRR, 2023
Uncertainty Quantification of Bandgaps in Acoustic Metamaterials with Stochastic Geometric Defects and Material Properties.
CoRR, 2023
SiamAF: Learning Shared Information from ECG and PPG Signals for Robust Atrial Fibrillation Detection.
CoRR, 2023
Learned Kernels for Interpretable and Efficient PPG Signal Quality Assessment and Artifact Segmentation.
CoRR, 2023
A Self-Supervised Algorithm for Denoising Photoplethysmography Signals for Heart Rate Estimation from Wearables.
CoRR, 2023
CoRR, 2023
CoRR, 2023
Understanding and Exploring the Whole Set of Good Sparse Generalized Additive Models.
CoRR, 2023
From Feature Importance to Distance Metric: An Almost Exact Matching Approach for Causal Inference.
CoRR, 2023
Proceedings of the Uncertainty in Artificial Intelligence, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
This Looks Like Those: Illuminating Prototypical Concepts Using Multiple Visualizations.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
The Rashomon Importance Distribution: Getting RID of Unstable, Single Model-based Variable Importance.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
A user interface to communicate interpretable AI decisions to radiologists (Erratum).
Proceedings of the Medical Imaging 2023: Image Perception, 2023
Proceedings of the Medical Imaging 2023: Image Perception, 2023
An Interpretable, Flexible, and Interactive Probabilistic Framework for Melody Generation.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023
Missing Values and Imputation in Healthcare Data: Can Interpretable Machine Learning Help?
Proceedings of the Conference on Health, Inference, and Learning, 2023
The Mechanical Bard: An Interpretable Machine Learning Approach to Shakespearean Sonnet Generation.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), 2023
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023
2022
J. Mach. Learn. Res., 2022
INFORMS J. Comput., 2022
A holistic approach to interpretability in financial lending: Models, visualizations, and summary-explanations.
Decis. Support Syst., 2022
CoRR, 2022
Fast Optimization of Weighted Sparse Decision Trees for use in Optimal Treatment Regimes and Optimal Policy Design.
CoRR, 2022
CoRR, 2022
CoRR, 2022
Why Interpretable Causal Inference is Important for High-Stakes Decision Making for Critically Ill Patients and How To Do It.
CoRR, 2022
TimberTrek: Exploring and Curating Sparse Decision Trees with Interactive Visualization.
Proceedings of the 2022 IEEE Visualization and Visual Analytics (VIS), 2022
Proceedings of the Uncertainty in Artificial Intelligence, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Interpretable deep learning models for better clinician-AI communication in clinical mammography.
Proceedings of the Medical Imaging 2022: Image Perception, 2022
Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022
Fast optimization of weighted sparse decision trees for use in optimal treatment regimes and optimal policy design.
Proceedings of the CIKM 2022 Workshops co-located with 31st ACM International Conference on Information and Knowledge Management (CIKM 2022), 2022
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022
2021
Trans. Assoc. Comput. Linguistics, 2021
A case-based interpretable deep learning model for classification of mass lesions in digital mammography.
Nat. Mach. Intell., 2021
Manag. Sci., 2021
J. Mach. Learn. Res., 2021
Understanding How Dimension Reduction Tools Work: An Empirical Approach to Deciphering t-SNE, UMAP, TriMap, and PaCMAP for Data Visualization.
J. Mach. Learn. Res., 2021
J. Artif. Intell. Res., 2021
CoRR, 2021
BacHMMachine: An Interpretable and Scalable Model for Algorithmic Harmonization for Four-part Baroque Chorales.
CoRR, 2021
Interpretable Mammographic Image Classification using Cased-Based Reasoning and Deep Learning.
CoRR, 2021
IAIA-BL: A Case-based Interpretable Deep Learning Model for Classification of Mass Lesions in Digital Mammography.
CoRR, 2021
CoRR, 2021
dame-flame: A Python Library Providing Fast Interpretable Matching for Causal Inference.
CoRR, 2021
Ethical Implementation of Artificial Intelligence to Select Embryos in In Vitro Fertilization.
Proceedings of the AIES '21: AAAI/ACM Conference on AI, 2021
2020
Nat. Mach. Intell., 2020
CoRR, 2020
In Pursuit of Interpretable, Fair and Accurate Machine Learning for Criminal Recidivism Prediction.
CoRR, 2020
Adaptive Hyper-box Matching for Interpretable Individualized Treatment Effect Estimation.
Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020
Proceedings of the 37th International Conference on Machine Learning, 2020
Proceedings of the 37th International Conference on Machine Learning, 2020
Proceedings of the FODS '20: ACM-IMS Foundations of Data Science Conference, 2020
PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020
Proceedings of the Second Workshop on Figurative Language Processing, 2020
Proceedings of the Second Workshop on Figurative Language Processing, 2020
2019
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead.
Nat. Mach. Intell., 2019
All Models are Wrong, but Many are Useful: Learning a Variable's Importance by Studying an Entire Class of Prediction Models Simultaneously.
J. Mach. Learn. Res., 2019
A study in Rashomon curves and volumes: A new perspective on generalization and model simplicity in machine learning.
CoRR, 2019
The Secrets of Machine Learning: Ten Things You Wish You Had Known Earlier to be More Effective at Data Analysis.
CoRR, 2019
Variable Importance Clouds: A Way to Explore Variable Importance for the Set of Good Models.
CoRR, 2019
Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019
Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019
Proceedings of the Seventh AAAI Conference on Human Computation and Crowdsourcing, 2019
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019
2018
Proceedings of the SysML Conference 2018, February, 2018
Math. Program. Comput., 2018
Optimized Scoring Systems: Toward Trust in Machine Learning for Healthcare and Criminal Justice.
Interfaces, 2018
CoRR, 2018
Shall I Compare Thee to a Machine-Written Sonnet? An Approach to Algorithmic Sonnet Generation.
CoRR, 2018
Collapsing-Fast-Large-Almost-Matching-Exactly: A Matching Method for Causal Inference.
CoRR, 2018
New Techniques for Preserving Global Structure and Denoising With Low Information Loss in Single-Image Super-Resolution.
Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2018
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018
Deep Learning for Case-Based Reasoning Through Prototypes: A Neural Network That Explains Its Predictions.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018
2017
J. Mach. Learn. Res., 2017
J. Mach. Learn. Res., 2017
CoRR, 2017
CoRR, 2017
Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017
Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017
Proceedings of the 34th International Conference on Machine Learning, 2017
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017
2016
Mach. Learn., 2016
Learning classification models of cognitive conditions from subtle behaviors in the digital Clock Drawing Test.
Mach. Learn., 2016
The Factorized Self-Controlled Case Series Method: An Approach for Estimating the Effects of Many Drugs on Many Outcomes.
J. Mach. Learn. Res., 2016
CoRR, 2016
Bayesian Inference of Arrival Rate and Substitution Behavior from Sales Transaction Data with Stockouts.
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016
Proceedings of the IEEE 16th International Conference on Data Mining, 2016
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016
2015
Generalization bounds for learning with linear, polygonal, quadratic and conic side knowledge.
Mach. Learn., 2015
Or's of And's for Interpretable Classification, with Application to Context-Aware Recommender Systems.
CoRR, 2015
Interpretable classifiers using rules and Bayesian analysis: Building a better stroke prediction model.
CoRR, 2015
Big Data, 2015
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015
2014
Tire Changes, Fresh Air, and Yellow Flags: Challenges in Predictive Analytics for Professional Racing.
Big Data, 2014
Proceedings of the 2014 SIAM International Conference on Data Mining, 2014
The Bayesian Case Model: A Generative Approach for Case-Based Reasoning and Prototype Classification.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014
Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014
Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014
Proceedings of the International Symposium on Artificial Intelligence and Mathematics, 2014
Proceedings of the International Symposium on Artificial Intelligence and Mathematics, 2014
Proceedings of the International Symposium on Artificial Intelligence and Mathematics, 2014
Proceedings of the 5th International Conference on Ambient Systems, 2014
2013
J. Mach. Learn. Res., 2013
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013
Proceedings of the Late-Breaking Developments in the Field of Artificial Intelligence, 2013
Proceedings of the Late-Breaking Developments in the Field of Artificial Intelligence, 2013
Proceedings of the Late-Breaking Developments in the Field of Artificial Intelligence, 2013
Proceedings of the Late-Breaking Developments in the Field of Artificial Intelligence, 2013
Proceedings of the Late-Breaking Developments in the Field of Artificial Intelligence, 2013
2012
IEEE Trans. Pattern Anal. Mach. Intell., 2012
Progressive Clustering with Learned Seeds: An Event Categorization System for Power Grid.
Proceedings of the 24th International Conference on Software Engineering & Knowledge Engineering (SEKE'2012), 2012
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012
Proceedings of the International Symposium on Artificial Intelligence and Mathematics, 2012
Proceedings of the Machine Aggregation of Human Judgment, 2012
2011
Proceedings of the COLT 2011, 2011
J. Mach. Learn. Res., 2011
Proceedings of the Algorithmic Decision Theory - Second International Conference, 2011
2010
2009
J. Mach. Learn. Res., 2009
The P-Norm Push: A Simple Convex Ranking Algorithm that Concentrates at the Top of the List.
J. Mach. Learn. Res., 2009
Proceedings of the International Conference on Machine Learning and Applications, 2009
Proceedings of the 12th IEEE International Conference on Computer Vision Workshops, 2009
Reducing Noise in Labels and Features for a Real World Dataset: Application of NLP Corpus Annotation Methods.
Proceedings of the Computational Linguistics and Intelligent Text Processing, 2009
2008
Arabic Morphological Tagging, Diacritization, and Lemmatization Using Lexeme Models and Feature Ranking.
Proceedings of the ACL 2008, 2008
2006
Proceedings of the Learning Theory, 19th Annual Conference on Learning Theory, 2006
2005
Proceedings of the Learning Theory, 18th Annual Conference on Learning Theory, 2005
2004
J. Mach. Learn. Res., 2004
Proceedings of the Learning Theory, 17th Annual Conference on Learning Theory, 2004
2003
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003