
Tong Wang 0011
Person information
- affiliation (PhD 2016): Massachusetts Institute of Technology, Cambridge, USA
Other persons with the same name
- Tong Wang — disambiguation page
- Tong Wang 0001
— Xidian University, National Laboratory of Radar Signal Processing, Xi'an, China
- Tong Wang 0002 — Concordia University, Montreal, Canada
- Tong Wang 0003
— Harbin Institute of Technology, Research Institute of Intelligent Control and Systems, China (and 1 more)
- Tong Wang 0004
— Nanjing University of Aeronautics and Astronautics, Department of Mathematics, China
- Tong Wang 0005
— Harbin Engineering University, College of Information and Communication Engineering, China
- Tong Wang 0006
— University of Edinburgh, Business School, UK
- Tong Wang 0007 — University of Massachusetts Boston, Department of Computer Science, MA, USA
- Tong Wang 0008
— Air Force Engineering University, School of Air and Missile Defense, Xi'an, China
- Tong Wang 0009
— Eindhoven University of Technology, The Netherlands
- Tong Wang 0010
— Harbin Institute of Technology, Shenzhen Graduate School, China (and 2 more)
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2010 – 2019
- 2018
- [i4]Chaofan Chen, Kangcheng Lin, Cynthia Rudin, Yaron Shaposhnik, Sijia Wang, Tong Wang:
An Interpretable Model with Globally Consistent Explanations for Credit Risk. CoRR abs/1811.12615 (2018) - 2017
- [j2]Tong Wang, Cynthia Rudin, Finale Doshi-Velez, Yimin Liu, Erica Klampfl, Perry MacNeille:
A Bayesian Framework for Learning Rule Sets for Interpretable Classification. J. Mach. Learn. Res. 18: 70:1-70:37 (2017) - [i3]Tong Wang, Cynthia Rudin:
Causal Rule Sets for Identifying Subgroups with Enhanced Treatment Effect. CoRR abs/1710.05426 (2017) - 2016
- [b1]Tong Wang:
Finding patterns in features and observations: new machine learning models with applications in computational criminology, marketing, and medicine. Massachusetts Institute of Technology, Cambridge, USA, 2016 - [c3]Tong Wang, Cynthia Rudin, Finale Doshi-Velez, Yimin Liu, Erica Klampfl, Perry MacNeille:
Bayesian Rule Sets for Interpretable Classification. ICDM 2016: 1269-1274 - 2015
- [j1]Tong Wang, Cynthia Rudin, Daniel Wagner, Rich Sevieri:
Finding Patterns with a Rotten Core: Data Mining for Crime Series with Cores. Big Data 3(1): 3-21 (2015) - [i2]Tong Wang, Cynthia Rudin, Finale Doshi-Velez, Yimin Liu, Erica Klampfl, Perry MacNeille:
Or's of And's for Interpretable Classification, with Application to Context-Aware Recommender Systems. CoRR abs/1504.07614 (2015) - [i1]Tong Wang, Cynthia Rudin:
Learning Optimized Or's of And's. CoRR abs/1511.02210 (2015) - 2013
- [c2]Tong Wang, Cynthia Rudin, Daniel Wagner, Rich Sevieri:
Detecting Patterns of Crime with Series Finder. AAAI (Late-Breaking Developments) 2013 - [c1]Tong Wang, Cynthia Rudin, Daniel Wagner, Rich Sevieri:
Learning to Detect Patterns of Crime. ECML/PKDD (3) 2013: 515-530
Coauthor Index

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