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ORCIDTong Wang 0011
Person information
- affiliation: University of Iowa, IA, USA
- affiliation (PhD 2016): Massachusetts Institute of Technology, Cambridge, USA
Other persons with the same name
- Tong Wang — disambiguation page
- Tong Wang 0001
![[0000-0002-2664-1354]](https://dblp.dagstuhl.de/img/orcid-mark.12x12.png "0000-0002-2664-1354")
— 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 (and 1 more)
- 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)
- Tong Wang 0012 — Microsoft Research, Montréal, Canada (and 2 more)
- Tong Wang 0013 — Donghua University, College of Information Sciences and Technology, Shanghai, China (and 3 more)
- Tong Wang 0014 — Microsoft Research Asia, Beijing, China (and 1 more)
- Tong Wang 0015 — Chinese Academy of Sciences, Institute of Automation, National Laboratory of Pattern Recognition, Beijing, China (and 1 more)
- Tong Wang 0016 — Shanghai Second Polytechnic University, School of Computer and Information Engineering, Shanghai, China
- Tong Wang 0017 — Wuhan University, State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan, China
- Tong Wang 0018 — Toshiba Corporation, Corporate Research and Development Center, Wireless System Laboratory, Kawasaki, Japan (and 1 more)
- Tong Wang 0019 — Shanxi Medical University, School of Public Health, Division of Health Statistics, Taiyuan, China
- Tong Wang 0020 — Dalian Maritime University, Navigation College, Dalian, China
- Tong Wang 0021 — Northwestern Polytechnical University, School of Astronautics, Research Center for Intelligent Robotics, Xi'an, China (and 1 more)
- Tong Wang 0022 — Southeast University, Laboratory of Image Science and Technology and Key Laboratory of Computer Network and Information Integration, Nanjing, China (and 1 more)
- Tong Wang 0023 — Changchun University of Science and Technology, School of Electronic Information Engineering, Changchun, China
- Tong Wang 0024 — Shenyang University of Technology, School of Electrical Engineering, Shenyang, China
- Tong Wang 0025 — Beihang University, School of Electronic and Information Engineering, Beijing, China (and 1 more)
- Tong Wang 0026 — Harbin Engineering University, College of Information and Communication Engineering, Harbin, China (and 1 more)
- Tong Wang 0027 — Shanghai Jiao Tong University, Antai College of Economics and Management, Shanghai, China
- Tong Wang 0028 — University of Science and Technology of China, School of Information Science and Technology, Hefei, China
- Tong Wang 0029 — University of Stuttgart, Institute of Signal Processing and System Theory, Stuttgart, Germany
- Tong Wang 0030 — Zhejiang University of Technology, College of Mechanical Engineering, Key Laboratory of E&M, Hangzhou, China
- Tong Wang 0031 — Lanzhou University of Technology, School of Computer and Communication, Lanzhou, China
- Tong Wang 0032 — Beijing Technology and Business University, Business School, Beijing, China
- Tong Wang 0033 — University of Illinois at Urbana-Champaign, Department of Physics, Woese Institute for Genomic Biology, Urbana, IL, USA
- Tong Wang 0034 — Beijing University of Civil Engineering and Architecture, School of Geomatics and Urban Spatial Informatics, Beijing, China
- Tong Wang 0035 — Shaanxi Provincial Natural Gas Co., Ltd., Xi'an, China
- Tong Wang 0036 — University of Tokyo, Graduate School of Information Science and Technology, Tokyo, Japan (and 1 more)
- Tong Wang 0037 — Shenyang Jianzhu University, School of Management, Shenyang, China
- Tong Wang 0038 — Harbin Normal University, Department of Geological Sciences, Harbin, China
- Tong Wang 0039 — Wuhan University, Computer School, Wuhan, China
- Tong Wang 0040 — Hubei University of Economics, Wuhan, Hubei, China
- Tong Wang 0041 — Alibaba Group, Hangzhou, China
- Tong Wang 0042 — Academy of Military Sciences, Beijing, China
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Books and Theses
- 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
Journal Articles
- 2022
- [j7]Chaofan Chen, Kangcheng Lin, Cynthia Rudin, Yaron Shaposhnik, Sijia Wang, Tong Wang:
A holistic approach to interpretability in financial lending: Models, visualizations, and summary-explanations. Decis. Support Syst. 152: 113647 (2022) - [j6]Tong Wang, Cynthia Rudin:
Causal Rule Sets for Identifying Subgroups with Enhanced Treatment Effects. INFORMS J. Comput. 34(3): 1626-1643 (2022) - [j5]Ronilo J. Ragodos, Tong Wang:
Disjunctive Rule Lists. INFORMS J. Comput. 34(6): 3259-3276 (2022) - [j4]Tong Wang, Cheng He, Fujie Jin, Yu (Jeffrey) Hu:
Evaluating the Effectiveness of Marketing Campaigns for Malls Using a Novel Interpretable Machine Learning Model. Inf. Syst. Res. 33(2): 659-677 (2022) - 2021
- [j3]Tong Wang, Qihang Lin:
Hybrid Predictive Models: When an Interpretable Model Collaborates with a Black-box Model. J. Mach. Learn. Res. 22: 137:1-137:38 (2021) - 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) - 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)
Conference and Workshop Papers
- 2024
- [c7]Yiyang Sun, Zhi Chen, Vittorio Orlandi, Tong Wang, Cynthia Rudin:
Sparse and Faithful Explanations Without Sparse Models. AISTATS 2024: 2071-2079 - [c6]Yiyang Sun, Tong Wang, Cynthia Rudin:
Improving Decision Sparsity. NeurIPS 2024 - 2022
- [c5]Ronilo J. Ragodos, Tong Wang, Qihang Lin, Xun Zhou:
ProtoX: Explaining a Reinforcement Learning Agent via Prototyping. NeurIPS 2022 - 2020
- [c4]Hassan Rafique, Tong Wang, Qihang Lin, Arshia Singhani:
Transparency Promotion with Model-Agnostic Linear Competitors. ICML 2020: 7898-7908 - 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 - 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
Informal and Other Publications
- 2024
- [i11]Yiyang Sun, Zhi Chen, Vittorio Orlandi, Tong Wang, Cynthia Rudin:
Sparse and Faithful Explanations Without Sparse Models. CoRR abs/2402.09702 (2024) - [i10]Yiyang Sun, Tong Wang, Cynthia Rudin:
Improving Decision Sparsity. CoRR abs/2410.20483 (2024) - 2022
- [i9]Ronilo J. Ragodos, Tong Wang, Qihang Lin, Xun Zhou:
ProtoX: Explaining a Reinforcement Learning Agent via Prototyping. CoRR abs/2211.03162 (2022) - 2021
- [i8]Chaofan Chen, Kangcheng Lin, Cynthia Rudin, Yaron Shaposhnik, Sijia Wang, Tong Wang:
A Holistic Approach to Interpretability in Financial Lending: Models, Visualizations, and Summary-Explanations. CoRR abs/2106.02605 (2021) - 2019
- [i7]Tong Wang, Qihang Lin:
Hybrid Predictive Model: When an Interpretable Model Collaborates with a Black-box Model. CoRR abs/1905.04241 (2019) - [i6]Hassan Rafique, Tong Wang, Qihang Lin:
Model-Agnostic Linear Competitors - When Interpretable Models Compete and Collaborate with Black-Box Models. CoRR abs/1909.10467 (2019) - [i5]Tong Wang, Fujie Jin, Yu (Jeffrey) Hu, Yuan Cheng:
Early Predictions for Medical Crowdfunding: A Deep Learning Approach Using Diverse Inputs. CoRR abs/1911.05702 (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
- [i3]Tong Wang, Cynthia Rudin:
Causal Rule Sets for Identifying Subgroups with Enhanced Treatment Effect. CoRR abs/1710.05426 (2017) - 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)
Coauthor Index
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