In which year was Rudin elected as a Fellow of the American Statistical Association and the Institute of Mathematical Statistics?
2019
Alina Jade Barnett et al.: A Case-Based Interpretable Deep Learning Model for Classification of Mass Lesions in Digital Mammography. (2021) authored by Cynthia Rudin. Zhi Chen et al.: How to See Hidden Patterns in Metamaterials with Interpretable Machine Learning. (2020) authored by Cynthia Rudin. Alina Jade Barnett et al.: Mapping the Ictal-Interictal-Injury Continuum Using Interpretable Machine Learning. (2017) authored by Cynthia Rudin. Yijie Bei et al.: New Techniques for Preserving Global Structure and Denoising with Low Information Loss in Single-Image Super-Resolution. (2018) authored by Cynthia Rudin. Alina Jade Barnett et al.: Interpretable deep learning models for better clinician-AI communication in clinical mammography. (2015) authored by Cynthia Rudin. Sully F. Chen et al.: Learned Kernels for Interpretable and Efficient PPG Signal Quality Assessment and Artifact Segmentation. (2023) authored by Cynthia Rudin. Zijie J. Wang et al.: TimberTrek: Exploring and Curating Sparse Decision Trees with Interactive Divya Koyyalagunta et al.: Playing Codenames with Language Graphs and Word Embeddings. (2020) authored by Cynthia Rudin. Han Zhang et al.: Uncertainty Quantification of Bandgaps in Acoustic Metamaterials with Stochastic Geometric Defects and Material Properties. (2023) authored by Cynthia Rudin. The Squirrel AI Award for Artificial Intelligence for the Benefit of Humanity was won in 2022 by the Association for the Advancement of Artificial Intelligence (AAAI). She is the author of "Stop Explaining Black Box Machine Learning Models for High Stakes Decisions and use Interpretable Models instead." and "Peter Hase et al.": An Interpretable and Scalable Model for Algorithmic Harmonization for Four-part Baroque Chorales. (2019) authored
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Question: In which year was Rudin elected as a Fellow of the American Statistical Association and the Institute of Mathematical Statistics?
Context: Alina Jade Barnett et al.: A Case-Based Interpretable Deep Learning Model for Classification of Mass Lesions in Digital Mammography. (2021) authored by Cynthia Rudin. Zhi Chen et al.: How to See Hidden Patterns in Metamaterials with Interpretable Machine Learning. (2020) authored by Cynthia Rudin. Alina Jade Barnett et al.: Mapping the Ictal-Interictal-Injury Continuum Using Interpretable Machine Learning. (2017) authored by Cynthia Rudin. Yijie Bei et al.: New Techniques for Preserving Global Structure and Denoising with Low Information Loss in Single-Image Super-Resolution. (2018) authored by Cynthia Rudin. Alina Jade Barnett et al.: Interpretable deep learning models for better clinician-AI communication in clinical mammography. (2015) authored by Cynthia Rudin. Sully F. Chen et al.: Learned Kernels for Interpretable and Efficient PPG Signal Quality Assessment and Artifact Segmentation. (2023) authored by Cynthia Rudin. Zijie J. Wang et al.: TimberTrek: Exploring and Curating Sparse Decision Trees with Interactive Divya Koyyalagunta et al.: Playing Codenames with Language Graphs and Word Embeddings. (2020) authored by Cynthia Rudin. Han Zhang et al.: Uncertainty Quantification of Bandgaps in Acoustic Metamaterials with Stochastic Geometric Defects and Material Properties. (2023) authored by Cynthia Rudin. The Squirrel AI Award for Artificial Intelligence for the Benefit of Humanity was won in 2022 by the Association for the Advancement of Artificial Intelligence (AAAI). She is the author of "Stop Explaining Black Box Machine Learning Models for High Stakes Decisions and use Interpretable Models instead." and "Peter Hase et al.": An Interpretable and Scalable Model for Algorithmic Harmonization for Four-part Baroque Chorales. (2019) authored
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