2 papers
cs.LG2024
Improving Decision Sparsity
Yiyang Sun, Tong Wang, Cynthia Rudin
Sparsity is a central aspect of interpretability in machine learning. Typically, sparsity is measured in terms of the size of a model globally, such as the number of variables it u…
cs.LG2024
Sparse and Faithful Explanations Without Sparse Models
Yiyang Sun, Zhi Chen, Vittorio Orlandi +2
Even if a model is not globally sparse, it is possible for decisions made from that model to be accurately and faithfully described by a small number of features. For instance, an…