Tong Wang - RankMe

27 papers A* 4A 1Journal 18Unranked 3

Year	Rank	Type	Title / Venue / Authors
2025	—	`conf`	ConPro-GAIL: Interpretable Policy Learning via Conceptual Prototyping for Human Spatiotemporal Decision Understanding. SIGSPATIAL/GIS Ronilo Ragodos, Xun Zhou, Tong Wang, Yajun Pan, Jun Luo
2024	A*	`conf`	Improving Decision Sparsity. NeurIPS Yiyang Sun, Tong Wang, Cynthia Rudin
2024	J	`jnl`	Improving Decision Sparsity. CoRR Yiyang Sun, Tong Wang, Cynthia Rudin
2024	A	`conf`	Sparse and Faithful Explanations Without Sparse Models. AISTATS Yiyang Sun, Zhi Chen, Vittorio Orlandi, Tong Wang, Cynthia Rudin
2024	J	`jnl`	Sparse and Faithful Explanations Without Sparse Models. CoRR Yiyang Sun, Zhi Chen, Vittorio Orlandi, Tong Wang, Cynthia Rudin
2022	J	`jnl`	A holistic approach to interpretability in financial lending: Models, visualizations, and summary-explanations. Decis. Support Syst. Chaofan Chen, Kangcheng Lin, Cynthia Rudin, Yaron Shaposhnik, Sijia Wang, Tong Wang
2022	J	`jnl`	Causal Rule Sets for Identifying Subgroups with Enhanced Treatment Effects. INFORMS J. Comput. Tong Wang, Cynthia Rudin
2022	J	`jnl`	Disjunctive Rule Lists. INFORMS J. Comput. Ronilo J. Ragodos, Tong Wang
2022	J	`jnl`	Evaluating the Effectiveness of Marketing Campaigns for Malls Using a Novel Interpretable Machine Learning Model. Inf. Syst. Res. Tong Wang, Cheng He, Fujie Jin, Yu (Jeffrey) Hu
2022	A*	`conf`	ProtoX: Explaining a Reinforcement Learning Agent via Prototyping. NeurIPS Ronilo J. Ragodos, Tong Wang, Qihang Lin, Xun Zhou
2022	J	`jnl`	ProtoX: Explaining a Reinforcement Learning Agent via Prototyping. CoRR Ronilo J. Ragodos, Tong Wang, Qihang Lin, Xun Zhou
2021	J	`jnl`	A Holistic Approach to Interpretability in Financial Lending: Models, Visualizations, and Summary-Explanations. CoRR Chaofan Chen, Kangcheng Lin, Cynthia Rudin, Yaron Shaposhnik, Sijia Wang, Tong Wang
2021	J	`jnl`	Hybrid Predictive Models: When an Interpretable Model Collaborates with a Black-box Model. J. Mach. Learn. Res. Tong Wang, Qihang Lin
2020	A*	`conf`	Transparency Promotion with Model-Agnostic Linear Competitors. ICML Hassan Rafique, Tong Wang, Qihang Lin, Arshia Singhani
2019	J	`jnl`	Early Predictions for Medical Crowdfunding: A Deep Learning Approach Using Diverse Inputs. CoRR Tong Wang, Fujie Jin, Yu (Jeffrey) Hu, Yuan Cheng
2019	J	`jnl`	Hybrid Predictive Model: When an Interpretable Model Collaborates with a Black-box Model. CoRR Tong Wang, Qihang Lin
2019	J	`jnl`	Model-Agnostic Linear Competitors - When Interpretable Models Compete and Collaborate with Black-Box Models. CoRR Hassan Rafique, Tong Wang, Qihang Lin
2018	J	`jnl`	An Interpretable Model with Globally Consistent Explanations for Credit Risk. CoRR Chaofan Chen, Kangcheng Lin, Cynthia Rudin, Yaron Shaposhnik, Sijia Wang, Tong Wang
2017	J	`jnl`	A Bayesian Framework for Learning Rule Sets for Interpretable Classification. J. Mach. Learn. Res. Tong Wang, Cynthia Rudin, Finale Doshi-Velez, Yimin Liu, Erica Klampfl, Perry MacNeille
2017	J	`jnl`	Causal Rule Sets for Identifying Subgroups with Enhanced Treatment Effect. CoRR Tong Wang, Cynthia Rudin
2016	A*	`conf`	Bayesian Rule Sets for Interpretable Classification. ICDM Tong Wang, Cynthia Rudin, Finale Doshi-Velez, Yimin Liu, Erica Klampfl, Perry MacNeille
2016	—	`—`	Finding patterns in features and observations: new machine learning models with applications in computational criminology, marketing, and medicine. Tong Wang
2015	J	`jnl`	Finding Patterns with a Rotten Core: Data Mining for Crime Series with Cores. Big Data Tong Wang, Cynthia Rudin, Daniel Wagner, Rich Sevieri
2015	J	`jnl`	Learning Optimized Or's of And's. CoRR Tong Wang, Cynthia Rudin
2015	J	`jnl`	Or's of And's for Interpretable Classification, with Application to Context-Aware Recommender Systems. CoRR Tong Wang, Cynthia Rudin, Finale Doshi-Velez, Yimin Liu, Erica Klampfl, Perry MacNeille
2013	—	`conf`	Detecting Patterns of Crime with Series Finder. AAAI (Late-Breaking Developments) Tong Wang, Cynthia Rudin, Daniel Wagner, Rich Sevieri
2013	—	`conf`	Learning to Detect Patterns of Crime. ECML/PKDD (3) Tong Wang, Cynthia Rudin, Daniel Wagner, Rich Sevieri