no code implementations • 3 Dec 2023 • Dennis Tang, Frank Willard, Ronan Tegerdine, Luke Triplett, Jon Donnelly, Luke Moffett, Lesia Semenova, Alina Jade Barnett, Jin Jing, Cynthia Rudin, Brandon Westover
In high-stakes medical applications, it is critical to have interpretable models so that experts can validate the reasoning of the model before making important diagnoses.
1 code implementation • 21 Nov 2023 • Chloe Qinyu Zhu, Muhang Tian, Lesia Semenova, Jiachang Liu, Jack Xu, Joseph Scarpa, Cynthia Rudin
Both of these have disadvantages: black box models are unacceptable for use in hospitals, whereas manual creation of models (including hand-tuning of logistic regression parameters) relies on humans to perform high-dimensional constrained optimization, which leads to a loss in performance.
no code implementations • NAACL (sdp) 2021 • Alex Oesterling, Angikar Ghosal, Haoyang Yu, Rui Xin, Yasa Baig, Lesia Semenova, Cynthia Rudin
The goal of the competition is to classify a citation in a scientific article based on its purpose.
no code implementations • 20 Mar 2021 • Cynthia Rudin, Chaofan Chen, Zhi Chen, Haiyang Huang, Lesia Semenova, Chudi Zhong
Interpretability in machine learning (ML) is crucial for high stakes decisions and troubleshooting.
no code implementations • 5 Aug 2019 • Lesia Semenova, Cynthia Rudin, Ronald Parr
We hypothesize that there is an important reason that simple-yet-accurate models often do exist.
1 code implementation • 22 Oct 2015 • Siong Thye Goh, Lesia Semenova, Cynthia Rudin
We present sparse tree-based and list-based density estimation methods for binary/categorical data.