Tong Wang

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Cynthia RudinProfessor of Computer Science, ECE, Statistics, and Biostatistics & Bioinformatics, Duke UniversityDirección de correo verificada de cs.duke.edu
Finale Doshi-VelezProfessor, HarvardDirección de correo verificada de seas.harvard.edu
Perry MacNeilleResearch Engineer, Ford Motor CompanyDirección de correo verificada de ford.com
Qihang LinThe University of IowaDirección de correo verificada de uiowa.edu
Yaron ShaposhnikUniversity of RochesterDirección de correo verificada de simon.rochester.edu
Kangcheng LinPh.D. Student, University of Illinois at Urbana-ChampaignDirección de correo verificada de illinois.edu
Ronilo RagodosUniversity of IowaDirección de correo verificada de uiowa.edu
Muriel MedardProfessor of EECS, MITDirección de correo verificada de mit.edu
Chaofan ChenAssistant Professor of Computer Science, University of MaineDirección de correo verificada de maine.edu
Dat HongNVIDIA CorporationDirección de correo verificada de nvidia.com
Yu Jeffrey HuProfessor, Accenture Chair, Purdue UniversityDirección de correo verificada de purdue.edu
Barrett W. ThomasProfessor, Department of Business Analytics, University of IowaDirección de correo verificada de uiowa.edu
Marlin W. UlmerProfessor of Management Science, Otto-von-Guericke-Universität MagdeburgDirección de correo verificada de ovgu.de
Fujie JinIndiana UniversityDirección de correo verificada de indiana.edu
Maytal Saar-TsechanskyThe University of Texas at AustinDirección de correo verificada de mccombs.utexas.edu
Stephen BaekAssociate Professor, University of VirginiaDirección de correo verificada de virginia.edu
Cheng HeUniversity of Wisconsin-MadisonDirección de correo verificada de wisc.edu
K SudhirJames Frank Professor of Marketing, Private Enterprise and Management, Yale SOMDirección de correo verificada de yale.edu

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Tong Wang

Yale University

Dirección de correo verificada de yale.edu - Página principal

interpretable machine learning reinforcement learning quantitative marketing


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
A Bayesian Framework for Learning Rule Sets for Interpretable Classification T Wang, C Rudin, F Doshi, Y Liu, E Klampfl, P MacNeille Journal of Machine Learning Research 18 (70), 1-37, 2017	395*	2017
Learning to detect patterns of crime T Wang, C Rudin, D Wagner, R Sevieri Joint European conference on machine learning and knowledge discovery in …, 2013	184	2013
A Holistic Approach to Interpretability in Financial Lending: Models, Visualizations, and Summary-Explanations C Chen, K Lin, C Rudin, Y Shaposhnik, S Wang, T Wang Decision Support Systems, 2021	170*	2021
Gaining Free or Low-Cost Transparency with Interpretable Partial Substitute T Wang International Conference on Machine Learning, 6505-6514, 2019	80*	2019
Hybrid Predictive Model: When an Interpretable Model Collaborates with a Black-box Model T Wang, Q Lin Journal of Machine Learning Research 22, 2021	55	2021
Same-day delivery with fair customer service X Chen, T Wang, BW Thomas, MW Ulmer European journal of operational research 308 (2), 738-751, 2023	54*	2023
On the design of network coding for multiple two-way relaying channels Z Ding, T Wang, M Peng, W Wang, KK Leung IEEE Transactions on Wireless Communications 10 (6), 1820-1832, 2011	53	2011
Outcomes associated with peripherally inserted central catheters in hospitalised children: a retrospective 7-year single-centre experience A Badheka, J Bloxham, A Schmitz, B Freyenberger, T Wang, S Rampa, ... BMJ open 9 (8), e026031, 2019	47	2019
Causal Rule Sets for Identifying Subgroups with Enhanced Treatment Effects T Wang, C Rudin INFORMS Journal on Computing, 2022	40*	2022
Finding patterns with a rotten core: Data mining for crime series with cores T Wang, C Rudin, D Wagner, R Sevieri Big Data 3 (1), 3-21, 2015	40	2015
Detecting patterns of crime with series finder T Wang, C Rudin, D Wagner, R Sevieri Twenty-Seventh AAAI Conference on Artificial Intelligence Late Breaking, 2013	39	2013
Paralanguage classifier (PARA): An algorithm for automatic coding of paralinguistic nonverbal parts of speech in text AW Luangrath, Y Xu, T Wang Journal of Marketing Research 60 (2), 388-408, 2023	35	2023
Multi-value Rule Sets for Interpretable Classification with Feature-Efficient Representations T Wang (NeurIPS) Conference on Neural Information Processing Systems, 10858--10868, 2018	35*	2018
Network coded storage with multi-resolution codes M Medard, UJ Ferner, T Wang US Patent 9,607,003, 2017	29	2017
Learning optimized Or's of And's T Wang, C Rudin arXiv preprint arXiv:1511.02210, 2015	29	2015
Protorynet-interpretable text classification via prototype trajectories D Hong, T Wang, S Baek Journal of Machine Learning Research 24 (264), 1-39, 2023	28*	2023
Dental anomaly detection using intraoral photos via deep learning R Ragodos, T Wang, C Padilla, JT Hecht, FA Poletta, IM Orioli, CJ Buxó, ... Scientific Reports 12 (1), 1-1, 2022	23	2022
Evaluating the Effectiveness of Marketing Campaigns for Malls Using A Novel Interpretable Machine Learning Model T Wang, C He, F Jin, YJ Hu Information Systems Research, 2021	22	2021
Interpretable Companions for Black-Box Models D Pan, T Wang, S Hara AISTATS, 2020	19	2020
Augmented Fairness: An Interpretable Model Augmenting Decision-Makers' Fairness T Wang, M Saar-Tsechansky arXiv preprint arXiv:2011.08398, 2020	14	2020

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