| An interpretable model with globally consistent explanations for credit risk C Chen, K Lin, C Rudin, Y Shaposhnik, S Wang, T Wang arXiv preprint arXiv:1811.12615, 2018 | 114 | 2018 |
| A holistic approach to interpretability in financial lending: Models, visualizations, and summary-explanations C Chen, K Lin, C Rudin, Y Shaposhnik, S Wang, T Wang Decision Support Systems 152, 113647, 2022 | 46 | 2022 |
| A simple rotational equivariance loss for generic convolutional segmentation networks: preliminary results K Lin, B Huang, LM Collins, K Bradbury, JM Malof IGARSS 2019-2019 IEEE International Geoscience and Remote Sensing Symposium …, 2019 | 7 | 2019 |
| An interpretable model with globally consistent explanations for credit risk. arXiv C Chen, K Lin, C Rudin, Y Shaposhnik, S Wang, T Wang arXiv preprint arXiv:1811.12615, 2018 | 4 | 2018 |
| Investigate the Influence of Online Ratings and Reviews in Purchase Behavior Using Customer Choice Sets K Lin, HM Kim International Design Engineering Technical Conferences and Computers and …, 2021 | 2 | 2021 |
| An automated method to conduct importance-performance analysis of product attributes from online reviews-an extension with a case study K Lin, H Kim Proceedings of the Design Society 1, 417-426, 2021 | 2 | 2021 |
| An explainable model for credit risk performance C Chen, K Lin, C Rudin, Y Shaposhnik, S Wang, T Wang Explainable Machine Learning Challenge documentation, 2018 | 2 | 2018 |
| Investigate Customer Preferences Using Online Video Reviews-Preliminary Results K Lin, H Kim International Design Engineering Technical Conferences and Computers and …, 2023 | | 2023 |
| INVESTIGATION OF CUSTOMER PREFERENCE CHANGES FOLLOWING COVID-19 MARKET DISRUPTION USING ONLINE REVIEW ANALYSIS S Park, K Lin, J Joung, H Kim Proceedings of the Design Society 3, 2375-2384, 2023 | | 2023 |
