83 citations · 123 across the 4 of their papers we have counts for
4 papers
Hybrid Predictive Model: When an Interpretable Model Collaborates with a Black-box Model
Tong Wang, Qihang Lin
Interpretable machine learning has become a strong competitor for traditional black-box models. However, the possible loss of the predictive performance for gaining interpretabilit…
Multi-Value Rule Sets
Tong Wang
We present the Multi-vAlue Rule Set (MARS) model for interpretable classification with feature efficient presentations. MARS introduces a more generalized form of association rules…
A Joint Model for Question Answering and Question Generation
Tong Wang, Xingdi Yuan, Adam Trischler
We propose a generative machine comprehension model that learns jointly to ask and answer questions based on documents. The proposed model uses a sequence-to-sequence framework tha…
Or's of And's for Interpretable Classification, with Application to Context-Aware Recommender Systems
Tong Wang, Cynthia Rudin, Finale Doshi-Velez +3
We present a machine learning algorithm for building classifiers that are comprised of a small number of disjunctions of conjunctions (or's of and's). An example of a classifier of…