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Cynthia D Rudin — all works

330 works · page 1 of 4 · 1–100 · ← Cynthia D Rudin

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  1. Stop Explaining Black Box Machine Learning Models for High Stakes Decisions and Use Interpretable Models InsteadNature Machine IntelligenceCynthia Rudin2018 · 10,460 citations
  2. All Models are Wrong, but Many are Useful: Learning a Variable's Importance by Studying an Entire Class of Prediction Models Simultaneously ↗arXiv (Cornell University) · no summary yetAaron Fisher, Cynthia D Rudin, Francesca Dominici2018 · 1,155 citations
  3. Interpretable classifiers using rules and Bayesian analysis: Building a better stroke prediction model ↗The Annals of Applied Statistics · no summary yetBenjamin Letham et al.2015 · 783 citations
  4. This Looks Like That: Deep Learning for Interpretable Image Recognition ↗arXiv (Cornell University) · no summary yetChaofan Chen et al.2018 · 590 citations
  5. Deep Learning for Case-Based Reasoning Through Prototypes: A Neural Network That Explains Its Predictions ↗Proceedings of the AAAI Conference on Artificial Intelligence · no summary yetOscar Li et al.2018 · 547 citations
  6. PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models ↗IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · no summary yetSachit Menon et al.2020 · 540 citations
  7. The Big Data Newsvendor: Practical Insights from Machine Learning ↗Operations Research · no summary yetGah‐Yi Ban, Cynthia D Rudin2018 · 508 citations
  8. Why Are We Using Black Box Models in AI When We Don’t Need To? A Lesson From An Explainable AI Competition ↗Harvard Data Science Review · no summary yetCynthia D Rudin, Joanna Radin2019 · 437 citations
  9. Supersparse linear integer models for optimized medical scoring systems ↗Machine Learning · no summary yetBerk Ustun, Cynthia D Rudin2015 · 335 citations
  10. Concept whitening for interpretable image recognition ↗Nature Machine Intelligence · no summary yetZhi Chen, Yijie Bei, Cynthia D Rudin2020 · 294 citations
  11. Machine Learning for the New York City Power Grid ↗IEEE Transactions on Pattern Analysis and Machine Intelligence · no summary yetCynthia D Rudin et al.2011 · 263 citations
  12. Understanding How Dimension Reduction Tools Work: An Empirical Approach to Deciphering t-SNE, UMAP, TriMAP, and PaCMAP for Data Visualization ↗arXiv (Cornell University) · no summary yetYingfan Wang et al.2020 · 252 citations
  13. Arabic Morphological Tagging, Diacritization, and Lemmatization Using Lexeme Models and Feature RankingRyan Roth, Owen Rambow, Nizar Habash, et al.Semitic languages · 217 citations
  14. A Shared Vision for Machine Learning in Neuroscience ↗Journal of Neuroscience · no summary yetMai-Anh T. Vu et al.2018 · 190 citations
  15. The Age of Secrecy and Unfairness in Recidivism Prediction ↗Harvard Data Science Review · no summary yetCynthia D Rudin, Caroline Wang, Beau Coker2018 · 183 citations
  16. Applied machine learning as a driver for polymeric biomaterials design ↗Nature Communications · no summary yetSamantha M. McDonald et al.2023 · 167 citations
  17. Learning classification models of cognitive conditions from subtle behaviors in the digital Clock Drawing Test ↗Machine Learning · no summary yetWilliam Souillard‐Mandar et al.2015 · 166 citations
  18. A case-based interpretable deep learning model for classification of mass lesions in digital mammography ↗Nature Machine Intelligence · no summary yetAlina Jade Barnett et al.2021 · 164 citations
  19. Interpretable Classification Models for Recidivism Prediction ↗Journal of the Royal Statistical Society Series A (Statistics in Society) · no summary yetJiaming Zeng, Berk Ustun, Cynthia D Rudin2016 · 162 citations
  20. Towards a comprehensive evaluation of dimension reduction methods for transcriptomic data visualization ↗Communications Biology · no summary yetHaiyang Huang et al.2022 · 148 citations
  21. Interpretable Image Recognition with Hierarchical Prototypes ↗Proceedings of the AAAI Conference on Human Computation and Crowdsourcing · no summary yetPeter Hase et al.2019 · 131 citations
  22. The Bayesian Case Model: A Generative Approach for Case-Based Reasoning and Prototype Classification ↗arXiv (Cornell University) · no summary yetBeen Kim, Cynthia D Rudin, Julie Shah2014 · 131 citations
  23. Optimized Scoring Systems: Toward Trust in Machine Learning for Healthcare and Criminal Justice ↗INFORMS Journal on Applied Analytics · no summary yetCynthia D Rudin, Berk Ustun2018 · 122 citations
  24. Learning to Detect Patterns of Crime ↗Lecture notes in computer science · no summary yetTong Wang et al.2013 · 120 citations
  25. Learning Certifiably Optimal Rule Lists for Categorical Data ↗arXiv (Cornell University) · no summary yetElaine Lee Angelino et al.2017 · 118 citations
  26. Machine learning for science and society ↗Machine Learning · no summary yetCynthia D Rudin, Kiri L. Wagstaff2013 · 116 citations
  27. In Pursuit of Interpretable, Fair and Accurate Machine Learning for Criminal Recidivism Prediction ↗Journal of Quantitative Criminology · no summary yetCaroline Wang et al.2022 · 106 citations
  28. Why black box machine learning should be avoided for high-stakes decisions, in brief ↗Nature Reviews Methods Primers · no summary yetCynthia D Rudin2022 · 105 citations
  29. Learning Certifiably Optimal Rule Lists ↗ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD) · no summary yetElaine Lee Angelino et al.2017 · 105 citations
  30. On the Existence of Simpler Machine Learning Models ↗ACM Conference on Fairness, Accountability, and Transparency (FAccT) · no summary yetLesia Semenova, Cynthia D Rudin, Ronald Parr2019 · 99 citations
  31. The Dynamics of AdaBoost: Cyclic Behavior and Convergence of Margins ↗no summary yetCynthia D Rudin, Ingrid C. Daubechies, Robert E. Schapire2004 · 89 citations
  32. Margin-Based Ranking Meets Boosting in the Middle ↗Lecture notes in computer science · no summary yetCynthia D Rudin et al.2005 · 69 citations
  33. An Interpretable Model with Globally Consistent Explanations for Credit Risk ↗arXiv (Cornell University) · no summary yetChaofan Chen et al.2018 · 65 citations
  34. AsymMirai: Interpretable Mammography-based Deep Learning Model for 1–5-year Breast Cancer Risk Prediction ↗Radiology · no summary yetJon P. Donnelly et al.2024 · 63 citations
  35. Generalized and Scalable Optimal Sparse Decision Trees ↗arXiv (Cornell University) · no summary yetLin, Jimmy et al.2020 · 61 citations
  36. A holistic approach to interpretability in financial lending: Models, visualizations, and summary-explanations ↗Decision Support Systems · no summary yetChaofan Chen et al.2021 · 60 citations
  37. Exploring the cloud of variable importance for the set of all good models ↗Nature Machine Intelligence · no summary yetJiayun Dong, Cynthia D Rudin2020 · 59 citations
  38. A process for predicting manhole events in Manhattan ↗Machine Learning · no summary yetCynthia D Rudin et al.2010 · 58 citations
  39. Ranking with a P-Norm Push ↗Lecture notes in computer science · no summary yetCynthia D Rudin2006 · 57 citations
  40. Learning Optimized Risk Scores ↗arXiv (Cornell University) · no summary yetBerk Ustun, Cynthia D Rudin2016 · 56 citations
  41. Learning customized and optimized lists of rules with mathematical programming ↗Mathematical Programming Computation · no summary yetCynthia D Rudin, Şeyda Ertekin2018 · 55 citations
  42. Learning Cost-Effective and Interpretable Treatment Regimes ↗International Conference on Artificial Intelligence and Statistics · no summary yetHimabindu Lakkaraju, Cynthia D Rudin2017 · 53 citations
  43. Optimized Risk Scores ↗ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD) · no summary yetBerk Ustun, Cynthia D Rudin2017 · 53 citations
  44. Sequential event prediction ↗Machine Learning · no summary yetBenjamin Letham, Cynthia D Rudin, David Madigan2013 · 53 citations
  45. Reactive point processes: A new approach to predicting power failures in underground electrical systems ↗The Annals of Applied Statistics · no summary yetŞeyda Ertekin, Cynthia D Rudin, Tyler H. McCormick2015 · 52 citations
  46. Online coordinate boosting ↗arXiv:0810.4553 · no summary yetRaphael A. Pelossof et al.2009 · 52 citations
  47. Interpretable algorithmic forensics ↗Proceedings of the National Academy of Sciences · no summary yetBrandon L. Garrett, Cynthia D Rudin2023 · 48 citations
  48. Bayesian Rule Sets for Interpretable Classification ↗Proceedings · no summary yetTong Wang et al.2016 · 46 citations
  49. Fast Sparse Decision Tree Optimization via Reference Ensembles ↗Proceedings of the AAAI Conference on Artificial Intelligence · no summary yetHayden McTavish et al.2022 · 45 citations
  50. Box drawings for learning with imbalanced data ↗ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD) · no summary yetSiong Thye Goh, Cynthia D Rudin2014 · 45 citations
  51. Bayesian hierarchical rule modeling for predicting medical conditions ↗The Annals of Applied Statistics · no summary yetTyler H. McCormick, Cynthia D Rudin, David Madigan2012 · 42 citations
  52. Prediction of tensile performance for 3D printed photopolymer gyroid lattices using structural porosity, base material properties, and machine learning ↗Materials & Design · no summary yetJacob Peloquin et al.2023 · 40 citations
  53. Metaphor Detection Using Contextual Word Embeddings From Transformers ↗Proceedings of the Second Workshop on Figurative Language Processing · no summary yetJerry Liu et al.2020 · 39 citations
  54. A Transformer Approach to Contextual Sarcasm Detection in TwitterWorkshop on Figurative Language ProcessingHunter Gregory, Steven Li, Pouya Mohammadi, et al.2020 · 38 citations
  55. Globally-Consistent Rule-Based Summary-Explanations for Machine Learning Models: Application to Credit-Risk Evaluation ↗SSRN Electronic Journal · no summary yetCynthia D Rudin, Yaron Shaposhnik2019 · 38 citations
  56. Exploring the Whole Rashomon Set of Sparse Decision Trees ↗PubMed · no summary yetRui Xin et al.2022 · 37 citations
  57. The Secrets of Machine Learning: Ten Things You Wish You Had Known Earlier to Be More Effective at Data Analysis ↗arXiv:1906.01998 · no summary yetCynthia D Rudin, David Carlson2019 · 37 citations
  58. Discovery with Data: Leveraging Statistics with Computer Science to Transform Science and Society ↗no summary yetCynthia D Rudin et al.2014 · 35 citations
  59. The rate of convergence of AdaBoost ↗Journal of Machine Learning Research · no summary yetIndraneel Mukherjee, Cynthia D Rudin, Robert E. Schapire2013 · 35 citations
  60. How to see hidden patterns in metamaterials with interpretable machine learning ↗Extreme Mechanics Letters · no summary yetZhi Chen et al.2022 · 34 citations
  61. New Techniques for Preserving Global Structure and Denoising with Low Information Loss in Single-Image Super-Resolution ↗IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · no summary yetYijie Bei et al.2018 · 34 citations
  62. Or's of And's for Interpretable Classification, with Application to Context-Aware Recommender Systems ↗arXiv (Cornell University) · no summary yetTong Wang et al.2015 · 32 citations
  63. On combining machine learning with decision making ↗Machine Learning · no summary yetTheja Tulabandhula, Cynthia D Rudin2014 · 32 citations
  64. Finding Patterns with a Rotten Core: Data Mining for Crime Series with Cores ↗Big Data · no summary yetTong Wang et al.2014 · 30 citations
  65. From Artificial Intelligence (AI) to Intelligence Augmentation (IA): Design Principles, Potential Risks, and Emerging Issues ↗AIS Transactions on Human-Computer Interaction · no summary yetLina Zhou et al.2023 · 29 citations
  66. Optimal Sparse Decision Trees ↗arXiv (Cornell University) · no summary yetXiyang Hu, Cynthia D Rudin, Margo Seltzer2019 · 29 citations
  67. FLAME: A Fast Large-scale Almost Matching Exactly Approach to Causal Inference ↗arXiv (Cornell University) · no summary yetTianyu Wang et al.2017 · 29 citations
  68. Analytics for Power Grid Distribution Reliability in New York City ↗INFORMS Journal on Applied Analytics · no summary yetCynthia D Rudin et al.2014 · 29 citations
  69. Methods and Models for Interpretable Linear Classification ↗arXiv (Cornell University) · no summary yetBerk Ustun, Cynthia D Rudin2014 · 28 citations
  70. Learning to Predict the Wisdom of Crowds ↗arXiv (Cornell University) · no summary yetŞeyda Ertekin, Haym Hirsh, Cynthia D Rudin2012 · 28 citations
  71. Analysis of boosting algorithms using the smooth margin function ↗The Annals of Statistics · no summary yetCynthia D Rudin, Robert E. Schapire, Ingrid C. Daubechies2007 · 28 citations
  72. Robust Optimization using Machine Learning for Uncertainty Sets ↗arXiv (Cornell University) · no summary yetTheja Tulabandhula, Cynthia D Rudin2014 · 26 citations
  73. Supersparse Linear Integer Models for Interpretable Classification ↗arXiv (Cornell University) · no summary yetBerk Ustun, Stefano Tracà, Cynthia D Rudin2013 · 25 citations
  74. SiamQuality: a ConvNet-based foundation model for photoplethysmography signals ↗Physiological Measurement · no summary yetCheng Ding et al.2024 · 24 citations
  75. TimberTrek: Exploring and Curating Sparse Decision Trees with Interactive Visualization ↗IEEE Visualization and Visual Analytics (VIS) · no summary yetZijie J. Wang et al.2022 · 24 citations
  76. Detecting patterns of crime with series finder ↗National Conference on Artificial Intelligence · no summary yetTong Wang et al.2013 · 23 citations
  77. Re-Ranking Algorithms for Name Tagging ↗Proceedings of the Workshop on Computationally Hard Problems and Joint Inference in Speech and Language Processing · no summary yetHeng Ji, Cynthia Rudin, Ralph Grishman2006 · 23 citations
  78. Boosting Based on a Smooth Margin ↗Lecture notes in computer science · no summary yetCynthia D Rudin, Robert E. Schapire, Ingrid C. Daubechies2004 · 23 citations
  79. FasterRisk: Fast and Accurate Interpretable Risk Scores ↗neural information processing systems · no summary yetJiachang Liu et al.2022 · 22 citations
  80. Integrated Single-cell Multiomic Analysis of HIV Latency Reversal Reveals Novel Regulators of Viral Reactivation ↗Genomics Proteomics & Bioinformatics · no summary yetManickam Ashokkumar et al.2024 · 20 citations
  81. A Theory of Statistical Inference for Ensuring the Robustness of Scientific Results ↗Management Science · no summary yetBeau Coker, Cynthia D Rudin, Gary King2018 · 20 citations
  82. Playing Codenames with Language Graphs and Word Embeddings ↗Journal of Artificial Intelligence Research · no summary yetDivya Koyyalagunta et al.2021 · 19 citations
  83. Sparse learned kernels for interpretable and efficient medical time series processing ↗Nature Machine Intelligence · no summary yetSully F. Chen et al.2024 · 18 citations
  84. Uncertainty quantification of acoustic metamaterial bandgaps with stochastic material properties and geometric defects ↗Computers & Structures · no summary yetHan Zhang et al.2024 · 18 citations
  85. An Optimization Approach to Learning Falling Rule Lists ↗arXiv (Cornell University) · no summary yetChaofan Chen, Cynthia D Rudin2017 · 18 citations
  86. Falling Rule Lists ↗International Conference on Artificial Intelligence and Statistics · no summary yetFulton Wang, Cynthia D Rudin2015 · 18 citations
  87. Ethical Implementation of Artificial Intelligence to Select Embryos in In Vitro Fertilization ↗Proceedings of the AAAI/ACM Conference on AI Ethics and Society · no summary yetMichael Anis Mihdi Afnan et al.2021 · 17 citations
  88. Causal Falling Rule Lists ↗arXiv (Cornell University) · no summary yetFulton Wang, Cynthia D Rudin2015 · 17 citations
  89. Equilibrium island ridge arrays in strained solid films ↗Journal of Applied Physics · no summary yetCynthia D Rudin, Brian J. Spencer1999 · 17 citations
  90. Interpretable Image Classification with Adaptive Prototype-based Vision Transformers ↗neural information processing systems · no summary yetChiyu Ma et al.2024 · 16 citations
  91. Amazing Things Come From Having Many Good Models ↗arXiv (Cornell University) · no summary yetCynthia D Rudin et al.2024 · 16 citations
  92. In Pursuit of Interpretable, Fair and Accurate Machine Learning for Criminal Recidivism Prediction ↗arXiv (Cornell University) · no summary yetWang, Caroline et al.2020 · 16 citations
  93. Interpretable Almost-Exact Matching for Causal Inference. ↗PubMed · no summary yetAwa Dieng et al.2019 · 16 citations
  94. Growing a list ↗Data Mining and Knowledge Discovery · no summary yetBenjamin Letham, Cynthia D Rudin, Katherine Heller2013 · 16 citations
  95. Data quality assurance and performance measurement of data mining for preventive maintenance of power grid ↗no summary yetLeon Wu et al.2011 · 16 citations
  96. This Looks Like Those: Illuminating Prototypical Concepts Using Multiple Visualizations ↗neural information processing systems · no summary yetChiyu Ma et al.2023 · 15 citations
  97. IAIA-BL: A Case-based Interpretable Deep Learning Model for Classification of Mass Lesions in Digital Mammography ↗arXiv (Cornell University) · no summary yetAlina Jade Barnett et al.2021 · 15 citations
  98. A Robust Approach to Quantifying Uncertainty in Matching Problems of Causal Inference ↗INFORMS Journal on Data Science · no summary yetMarco Morucci, Md. Noor‐E‐Alam, Cynthia D Rudin2018 · 15 citations
  99. Scalable Bayesian Rule Lists ↗arXiv (Cornell University) · no summary yetHongyu Yang, Cynthia D Rudin, Margo Seltzer2016 · 15 citations
  100. Learning Optimized Or's of And's ↗arXiv (Cornell University) · no summary yetTong Wang, Cynthia D Rudin2015 · 15 citations

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