| Session | Interpretable Systems in Machine Learning, Data Analysis, and Visualization |
| Chair | Michael Biehl |
| Co-Chair | Nitesh Chawla |
| Interpretable Models from Distributed Data Via Merging of Decision Trees |
| Regularization and Improved Interpretation of Linear Data Mappings and Adaptive Distance Measures |
| Quantitative Measurements of Model Interpretability for the Analysis of Spectral Data |
| Automated Selection of Interaction Effects in Sparse Kernel Methods to Predict Pregnancy Viability |
| Interpreting Individual Classifications of Hierarchical Networks |
