A group of students will read papers on case influence, model sensitivity and related topics.
- Case Influence and Model Complexity in Regression and Classification by Shanshan Tu
- Influence analysis based on the case sensitivity function by Critchley et al.
- General conditions for predictivity in learning theory by Poggio et al.
- The unreasonable effectiveness of deep learning in artificial intelligence by Terry Sejnowski
- Understanding Black-box Predictions via Influence Function by Koh and Liang
- Data Shapley: Equitable Valuation of Data for Machine Learning by Ghorbani and Zou
- Sobol’ Indices and Shapley Value by Art Owen
