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ORCIDGlenn Fung
Glenn Moo Fung – Glenn Martin Fung
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- affiliation: American Family Insurance, Madison, WI, USA
- affiliation: University of Wisconsin-Madison, Grainger Institute for Engineering, WI, USA
- affiliation: Siemens Medical Solutions, Malvern, PA, USA
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2020 – today
- 2023
[j23]Jeffery Kline
, Glenn Martin Fung:
Linear programming with nonparametric penalty programs and iterated thresholding. Optim. Methods Softw. 38(1): 107-127 (2023)- [c64]Ronak Mehta, Jeffery Kline, Vishnu Suresh Lokhande, Glenn Fung, Vikas Singh:
Efficient Discrete Multi Marginal Optimal Transport Regularization. ICLR 2023 - 2022
- [c63]Ender Tekin, Qian You, Devin M. Conathan, Glenn Moo Fung, Thomas S. Kneubuehl:
Harvest - a System for Creating Structured Rate Filing Data from Filing PDFs. AAAI 2022: 12414-12422 - [c62]Zhanpeng Zeng, Sourav Pal, Jeffery Kline, Glenn Moo Fung, Vikas Singh:
Multi Resolution Analysis (MRA) for Approximate Self-Attention. ICML 2022: 25955-25972 - [i14]Zhanpeng Zeng, Sourav Pal, Jeffery Kline, Glenn Moo Fung, Vikas Singh:
Multi Resolution Analysis (MRA) for Approximate Self-Attention. CoRR abs/2207.10284 (2022) - 2021
- [j22]Glenn Fung, Luisa F. Polanía, Sou-Cheng T. Choi, Victor Wu, Lawrence Ma:
Editorial: Artificial Intelligence in Insurance and Finance. Frontiers Appl. Math. Stat. 7: 795207 (2021) - [j21]Saravanan Thirumuruganathan, Han Li, Nan Tang, Mourad Ouzzani, Yash Govind, Derek Paulsen, Glenn Fung, AnHai Doan:
Deep Learning for Blocking in Entity Matching: A Design Space Exploration. Proc. VLDB Endow. 14(11): 2459-2472 (2021) - [c61]Yunyang Xiong, Zhanpeng Zeng, Rudrasis Chakraborty, Mingxing Tan, Glenn Fung, Yin Li, Vikas Singh:
Nyströmformer: A Nyström-based Algorithm for Approximating Self-Attention. AAAI 2021: 14138-14148 - [c60]Zachary Zhou, Jeffery Kline, Devin Conathan, Glenn Fung:
Low Resource Quadratic Forms for Knowledge Graph Embeddings. SustaiNLP@EMNLP 2021: 1-10 - [c59]Zhanpeng Zeng, Yunyang Xiong, Sathya N. Ravi, Shailesh Acharya, Glenn Moo Fung, Vikas Singh:
You Only Sample (Almost) Once: Linear Cost Self-Attention Via Bernoulli Sampling. ICML 2021: 12321-12332 - [c58]Ananth Raj GV, Qian You, Daniel Dickinson, Eric Bunch, Glenn Fung:
Document Classification and Information Extraction framework for Insurance Applications. TransAI 2021: 8-16 - [c57]Dan Dickinson, Ananth Raj GV, Glenn Fung:
A Model for Zero-shot Text Multi-labeling Using Semantics-based Labels. TransAI 2021: 147-154 - [i13]Teja Kanchinadam, Zihang Meng, Joseph Bockhorst, Vikas Singh, Glenn Fung:
Graph Neural Networks to Predict Customer Satisfaction Following Interactions with a Corporate Call Center. CoRR abs/2102.00420 (2021) - [i12]Teja Kanchinadam, Qian You, Keith Westpfahl, James Kim, Siva Gunda, Sebastian Seith, Glenn Fung:
A Simple yet Brisk and Efficient Active Learning Platform for Text Classification. CoRR abs/2102.00426 (2021) - [i11]Yunyang Xiong, Zhanpeng Zeng, Rudrasis Chakraborty, Mingxing Tan, Glenn Fung, Yin Li, Vikas Singh:
Nyströmformer: A Nyström-Based Algorithm for Approximating Self-Attention. CoRR abs/2102.03902 (2021) - [i10]Eric Bunch, Jeffery Kline, Daniel Dickinson, Suhaas Bhat, Glenn Fung:
Weighting vectors for machine learning: numerical harmonic analysis applied to boundary detection. CoRR abs/2106.00827 (2021) - [i9]Jaya Krishna Mandivarapu, Eric Bunch, Qian You, Glenn Fung:
Efficient Document Image Classification Using Region-Based Graph Neural Network. CoRR abs/2106.13802 (2021) - [i8]Jaya Krishna Mandivarapu, Eric Hunch, Glenn Fung:
Domain Agnostic Few-Shot Learning For Document Intelligence. CoRR abs/2111.00007 (2021) - [i7]Zhanpeng Zeng, Yunyang Xiong, Sathya N. Ravi, Shailesh Acharya, Glenn Fung, Vikas Singh:
You Only Sample (Almost) Once: Linear Cost Self-Attention Via Bernoulli Sampling. CoRR abs/2111.09714 (2021) - 2020
- [j20]Maleeha Qazi, Kaya Tollas, Teja Kanchinadam, Joseph Bockhorst, Glenn Fung:
Designing and deploying insurance recommender systems using machine learning. WIREs Data Mining Knowl. Discov. 10(4) (2020) - [c56]Sathya N. Ravi, Abhay Venkatesh, Glenn Moo Fung, Vikas Singh:
Optimizing Nondecomposable Data Dependent Regularizers via Lagrangian Reparameterization Offers Significant Performance and Efficiency Gains. AAAI 2020: 5487-5494 - [c55]Shailesh Acharya, Glenn Fung:
Using Optimal Embeddings to Learn New Intents with Few Examples: An Application in the Insurance Domain. Converse@KDD 2020 - [c54]Eric Bunch, Qian You, Glenn Fung:
Human-In-The-Loop Topic Discovery with Embedded Text Representations. DaSH@KDD 2020 - [c53]Teja Kanchinadam, Keith Westpfahl, Qian You, Glenn Fung:
Rationale-based Human-in-the-Loop via Supervised Attention. DaSH@KDD 2020 - [i6]Eric Bunch, Daniel Dickinson, Jeffery Kline, Glenn Fung:
Practical applications of metric space magnitude and weighting vectors. CoRR abs/2006.14063 (2020) - [i5]Victor Luo, Yazhen Wang, Glenn Fung:
SGD Distributional Dynamics of Three Layer Neural Networks. CoRR abs/2012.15036 (2020)
2010 – 2019
- 2019
- [j19]Shailesh Acharya, Glenn Fung:
Mileage Extraction From Odometer Pictures for Automating Auto Insurance Processes. Frontiers Appl. Math. Stat. 5: 61 (2019) - [j18]Sukrat Gupta, Teja Kanchinadam, Devin Conathan, Glenn Fung:
Task-Optimized Word Embeddings for Text Classification Representations. Frontiers Appl. Math. Stat. 5: 67 (2019) - [c52]Joseph Bockhorst, Devin Conathan, Glenn Moo Fung:
Probabilistic-Logic Bots for Efficient Evaluation of Business Rules Using Conversational Interfaces. AAAI 2019: 9422-9427 - [c51]Maleeha Qazi, Srinivas Tunuguntla, Peng Lee, Teja Kanchinadam, Glenn Fung, Neeraj Arora:
Discovering Temporal Patterns from Insurance Interaction Data. AAAI 2019: 9573-9580 - [c50]Yash Govind, Pradap Konda, Paul Suganthan G. C., Philip Martinkus, Palaniappan Nagarajan, Han Li, Aravind Soundararajan, Sidharth Mudgal, Jeffrey R. Ballard, Haojun Zhang, Adel Ardalan, Sanjib Das, Derek Paulsen, Amanpreet Singh Saini, Erik Paulson, Youngchoon Park, Marshall Carter, Mingju Sun, Glenn Moo Fung, AnHai Doan:
Entity Matching Meets Data Science: A Progress Report from the Magellan Project. SIGMOD Conference 2019: 389-403 - [c49]Luisa F. Polanía, Glenn Fung, Dongning Wang:
Ordinal Regression Using Noisy Pairwise Comparisons for Body Mass Index Range Estimation. WACV 2019: 782-790 - [i4]Sathya N. Ravi, Abhay Venkatesh, Glenn Moo Fung, Vikas Singh:
Optimizing Nondecomposable Data Dependent Regularizers via Lagrangian Reparameterization offers Significant Performance and Efficiency Gains. CoRR abs/1909.12398 (2019) - 2018
- [j17]Yash Govind, Erik Paulson, Palaniappan Nagarajan, Paul Suganthan G. C., AnHai Doan, Youngchoon Park, Glenn Fung, Devin Conathan, Marshall Carter, Mingju Sun:
CloudMatcher: A Hands-Off Cloud/Crowd Service for Entity Matching. Proc. VLDB Endow. 11(12): 2042-2045 (2018) - [c48]Zihang Meng, Nagesh Adluru, Hyunwoo J. Kim, Glenn Fung, Vikas Singh:
Efficient Relative Attribute Learning Using Graph Neural Networks. ECCV (14) 2018: 575-590 - [c47]Teja Kanchinadam, Maleeha Qazi, Joseph Bockhorst, Mary Y. Morell, Katie J. Meissner, Glenn Fung:
Using Discriminative Graphical Models for Insurance Recommender Systems. ICMLA 2018: 421-428 - [i3]Luisa F. Polanía, Dongning Wang, Glenn Fung:
Ordinal Regression using Noisy Pairwise Comparisons for Body Mass Index Range Estimation. CoRR abs/1811.03268 (2018) - 2017
- [c46]Joseph Bockhorst, Shi Yu, Luisa F. Polanía, Glenn Fung:
Predicting Self-reported Customer Satisfaction of Interactions with a Corporate Call Center. ECML/PKDD (3) 2017: 179-190 - [c45]Maleeha Qazi, Glenn Moo Fung, Katie J. Meissner, Eduardo R. Fontes:
An Insurance Recommendation System Using Bayesian Networks. RecSys 2017: 274-278 - 2016
- [j16]Glenn Fung, Olvi L. Mangasarian:
Unsupervised and Semisupervised Classification Via Absolute Value Inequalities. J. Optim. Theory Appl. 168(2): 551-558 (2016) - [c44]Joe Bockhorst, Yingjian Wang, Sukrat Gupta, Maleeha Qazi, Mingju Sun, Glenn Fung:
Using Temporal Discovery and Data-Driven Journey-Maps to Predict Customer Satisfaction. ICMLA 2016: 846-852 - [i2]Ramanathan Subramanian, Rómer Rosales, Glenn Fung, Jennifer G. Dy:
Evaluating Crowdsourcing Participants in the Absence of Ground-Truth. CoRR abs/1605.09432 (2016) - 2015
- [j15]Shipeng Yu, Faisal Farooq, Alexander Van Esbroeck, Glenn Fung, Vikram Anand, Balaji Krishnapuram:
Predicting readmission risk with institution-specific prediction models. Artif. Intell. Medicine 65(2): 89-96 (2015) - 2014
- [j14]Yan Yan, Rómer Rosales, Glenn Fung, Subramanian Ramanathan, Jennifer G. Dy:
Learning from multiple annotators with varying expertise. Mach. Learn. 95(3): 291-327 (2014) - [c43]Yan Yan, Rómer Rosales, Glenn Fung, Jennifer G. Dy:
Active learning from uncertain crowd annotations. Allerton 2014: 385-392 - 2013
- [j13]Glenn Fung, Olvi L. Mangasarian:
Privacy-preserving linear and nonlinear approximation via linear programming. Optim. Methods Softw. 28(1): 207-216 (2013) - [c42]Shipeng Yu, Alexander Van Esbroeck, Faisal Farooq, Glenn Fung, Vikram Anand, Balaji Krishnapuram:
Predicting Readmission Risk with Institution Specific Prediction Models. ICHI 2013: 415-420 - 2012
- [c41]Shipeng Yu, Faisal Farooq, Glenn Fung, Balaji Krishnapuram, Alexander Van Esbroeck, Vikram Anand:
Building Hospital-Specific Readmission Risk Prediction Models for Heart Failure, Acute Myocardial Infarction and Pneumonia patients. AMIA 2012 - [c40]Yan Yan, Rómer Rosales, Glenn Fung, Faisal Farooq, Bharat Rao, Jennifer G. Dy:
Active Learning from Multiple Knowledge Sources. AISTATS 2012: 1350-1357 - [i1]Yan Yan, Rómer Rosales, Glenn Fung, Jennifer G. Dy:
Modeling Multiple Annotator Expertise in the Semi-Supervised Learning Scenario. CoRR abs/1203.3529 (2012) - 2011
- [j12]Glenn Fung, O. L. Mangasarian:
Equivalence of Minimal ℓ0- and ℓp-Norm Solutions of Linear Equalities, Inequalities and Linear Programs for Sufficiently Small p. J. Optim. Theory Appl. 151(1): 1-10 (2011) - [c39]Yan Yan, Rómer Rosales, Glenn Fung, Jennifer G. Dy:
Active Learning from Crowds. ICML 2011: 1161-1168 - 2010
- [c38]Mahdokht Masaeli, Glenn Fung, Jennifer G. Dy:
From Transformation-Based Dimensionality Reduction to Feature Selection. ICML 2010: 751-758 - [c37]Yan Yan, Glenn Fung, Jennifer G. Dy, Rómer Rosales:
Medical coding classification by leveraging inter-code relationships. KDD 2010: 193-202 - [c36]Mahdokht Masaeli, Yan Yan, Ying Cui, Glenn Fung, Jennifer G. Dy:
Convex Principal Feature Selection. SDM 2010: 619-628 - [c35]Yan Yan, Rómer Rosales, Glenn Fung, Jennifer G. Dy:
Modeling Multiple Annotator Expertise in the Semi-Supervised Learning Scenario. UAI 2010: 674-682 - [c34]Yan Yan, Rómer Rosales, Glenn Fung, Mark Schmidt, Gerardo Hermosillo Valadez, Luca Bogoni, Linda Moy, Jennifer G. Dy:
Modeling annotator expertise: Learning when everybody knows a bit of something. AISTATS 2010: 932-939
2000 – 2009
- 2009
- [j11]Volkan Vural, Glenn Fung, Balaji Krishnapuram, Jennifer G. Dy, R. Bharat Rao:
Using Local Dependencies within Batches to Improve Large Margin Classifiers. J. Mach. Learn. Res. 10: 183-206 (2009) - [j10]Olvi L. Mangasarian, Edward W. Wild, Glenn Fung:
Proximal Knowledge-based Classification. Stat. Anal. Data Min. 1(4): 215-222 (2009) - [c33]Andre Dekker, Cary Dehing-Oberije, Dirk De Ruysscher, Philippe Lambin, Kartik Komati, Glenn Fung, Shipeng Yu, Andrew Hope, Wilfried De Neve, Yolande Lievens:
Survival Prediction in Lung Cancer Treated with Radiotherapy: Bayesian Networks vs. Support Vector Machines in Handling Missing Data. ICMLA 2009: 494-497 - [c32]Volkan Vural, Glenn Fung, Rómer Rosales, Jennifer G. Dy:
Multi-Class Classifiers and their Underlying Shared Structure. IJCAI 2009: 1267-1272 - 2008
- [j9]Volkan Vural, Glenn Fung, Jennifer G. Dy, Bharat Rao:
Fast semi-supervised SVM classifiers using a priori metric information. Optim. Methods Softw. 23(4): 521-532 (2008) - [j8]Murat Dundar, Glenn Fung, Balaji Krishnapuram, R. Bharat Rao:
Multiple-Instance Learning Algorithms for Computer-Aided Detection. IEEE Trans. Biomed. Eng. 55(3): 1015-1021 (2008) - [j7]Olvi L. Mangasarian, Edward W. Wild, Glenn Fung:
Privacy-preserving classification of vertically partitioned data via random kernels. ACM Trans. Knowl. Discov. Data 2(3): 12:1-12:16 (2008) - [c31]Glenn Fung, Sriram Krishnan, R. Bharat Rao, Hui Chen:
Learning Sparse Kernels from 3D Surfaces for Heart Wall Motion Abnormality Detection. AAAI 2008: 1663-1670 - [c30]Mark Schmidt, Kevin P. Murphy, Glenn Fung, Rómer Rosales:
Structure learning in random fields for heart motion abnormality detection. CVPR 2008 - [c29]Shipeng Yu, Glenn Fung, Rómer Rosales, Sriram Krishnan, R. Bharat Rao, Cary Dehing-Oberije, Philippe Lambin:
Privacy-preserving cox regression for survival analysis. KDD 2008: 1034-1042 - [c28]Philippe Bamberger, Isaac Leichter, Nicolas Merlet, Eli Ratner, Glenn Fung, Richard Lederman:
Optimizing the CAD Process for Detecting Mammographic Lesions by a New Generation Algorithm Using Linear Classifiers and a Gradient Based Approach. Digital Mammography / IWDM 2008: 358-365 - [c27]Isaac Leichter, Richard Lederman, Eli Ratner, Nicolas Merlet, Glenn Fung, Balaji Krishnapuram, Philippe Bamberger:
Does a Mammography CAD Algorithm with Varying Filtering Levels of Detection Marks, Used to Reduce the False Mark Rate, Adversely Affect the Detection of Small Masses?. Digital Mammography / IWDM 2008: 504-509 - [c26]R. Bharat Rao, Glenn Fung:
On the Dangers of Cross-Validation. An Experimental Evaluation. SDM 2008: 588-596 - [p1]Glenn Fung, Sathyakama Sandilya, R. Bharat Rao:
Rule Extraction from Linear Support Vector Machines via Mathematical Programming. Rule Extraction from Support Vector Machines 2008: 83-107 - 2007
- [j6]Glenn Fung, Jonathan Stoeckel:
SVM feature selection for classification of SPECT images of Alzheimer's disease using spatial information. Knowl. Inf. Syst. 11(2): 243-258 (2007) - [c25]Mark Schmidt, Glenn Fung, Rómer Rosales:
Fast Optimization Methods for L1 Regularization: A Comparative Study and Two New Approaches. ECML 2007: 286-297 - [c24]Glenn Fung, Renaud Seigneuric, Sriram Krishnan, R. Bharat Rao, Brad G. Wouters, Philippe Lambin:
Reducing a Biomarkers List via Mathematical Programming: Application to Gene Signatures to Detect Time-Dependent Hypoxia in Cancer. ICMLA 2007: 482-487 - [c23]Maleeha Qazi, Glenn Fung, Sriram Krishnan, Rómer Rosales, Harald Steck, R. Bharat Rao, Don Poldermans, Dhanalakshmi Chandrasekaran:
Automated Heart Wall Motion Abnormality Detection from Ultrasound Images Using Bayesian Networks. IJCAI 2007: 519-525 - [c22]Glenn Fung, Rómer Rosales, R. Bharat Rao:
Feature Selection and Kernel Design via Linear Programming. IJCAI 2007: 786-791 - [c21]R. Bharat Rao, Jinbo Bi, Glenn Fung, Marcos Salganicoff, Nancy Obuchowski, David P. Naidich:
LungCAD: a clinically approved, machine learning system for lung cancer detection. KDD 2007: 1033-1037 - 2006
- [j5]Glenn Fung, O. L. Mangasarian:
Breast Tumor Susceptibility to Chemotherapy Via Support Vector Machines. Comput. Manag. Sci. 3(2): 103-112 (2006) - [c20]Volkan Vural, Glenn Fung, Balaji Krishnapuram, Jennifer G. Dy, R. Bharat Rao:
Batch Classification with Applications in Computer Aided Diagnosis. ECML 2006: 449-460 - [c19]Rómer Rosales, Glenn Fung:
Learning sparse metrics via linear programming. KDD 2006: 367-373 - [c18]Jinbo Bi, Senthil Periaswamy, Kazunori Okada, Toshiro Kubota, Glenn Fung, Marcos Salganicoff, R. Bharat Rao:
Computer aided detection via asymmetric cascade of sparse hyperplane classifiers. KDD 2006: 837-844 - [c17]Glenn Fung, Balaji Krishnapuram, Nicolas Merlet, Eli Ratner, Philippe Bamberger, Jonathan Stoeckel, R. Bharat Rao:
Addressing Image Variability While Learning Classifiers for Detecting Clusters of Micro-calcifications. Digital Mammography / IWDM 2006: 84-91 - [c16]Glenn Fung, Murat Dundar, Balaji Krishnapuram, R. Bharat Rao:
Multiple Instance Learning for Computer Aided Diagnosis. NIPS 2006: 425-432 - 2005
- [j4]Glenn Fung, Olvi L. Mangasarian:
Multicategory Proximal Support Vector Machine Classifiers. Mach. Learn. 59(1-2): 77-97 (2005) - [c15]Jonathan Stoeckel, Glenn Fung:
SVM Feature Selection for Classification of SPECT Images of Alzheimer's Disease Using Spatial Information. ICDM 2005: 410-417 - [c14]Jinbo Bi, Glenn Fung, Murat Dundar, R. Bharat Rao:
Semi-Supervised Mixture of Kernels via LPBoost Methods. ICDM 2005: 569-572 - [c13]Glenn Fung, Maleeha Qazi, Sriram Krishnan, Jinbo Bi, R. Bharat Rao, A. Katz:
Sparse classifiers for Automated HeartWall Motion Abnormality Detection. ICMLA 2005: 194-200 - [c12]Glenn Fung, Sathyakama Sandilya, R. Bharat Rao:
Rule extraction from linear support vector machines. KDD 2005: 32-40 - [c11]Glenn Fung, Rómer Rosales, Balaji Krishnapuram:
Learning Rankings via Convex Hull Separation. NIPS 2005: 395-402 - [c10]Murat Dundar, Glenn Fung, Jinbo Bi, Sathyakama Sandilya, R. Bharat Rao:
Sparse Fisher Discriminant Analysis for Computer Aided Detection. SDM 2005: 476-480 - 2004
- [j3]Glenn Fung, O. L. Mangasarian:
A Feature Selection Newton Method for Support Vector Machine Classification. Comput. Optim. Appl. 28(2): 185-202 (2004) - [c9]Pascal Cathier, Senthil Periaswamy, Anna K. Jerebko, Murat Dundar, Jianming Liang, Glenn Fung, Jonathan Stoeckel, T. Venkata, R. Amara, Arun Krishnan, R. Bharat Rao, Alok Gupta, E. Vega, Shaked Laks, A. Megibow, Michael Macari, Luca Bogoni:
CAD for polyp detection: an invaluable tool to meet the increasing need for colon-cancer screening. CARS 2004: 978-982 - [c8]Murat Dundar, Glenn Fung, Luca Bogoni, Michael Macari, A. Megibow, R. Bharat Rao:
A methodology for training and validating a CAD system and potential pitfalls. CARS 2004: 1010-1014 - [c7]Glenn Fung, Murat Dundar, Jinbo Bi, R. Bharat Rao:
A fast iterative algorithm for fisher discriminant using heterogeneous kernels. ICML 2004 - 2003
- [j2]Glenn Fung, Olvi L. Mangasarian:
Finite Newton method for Lagrangian support vector machine classification. Neurocomputing 55(1-2): 39-55 (2003) - [c6]Glenn Fung, Olvi L. Mangasarian, Jude W. Shavlik:
Knowledge-Based Nonlinear Kernel Classifiers. COLT 2003: 102-113 - [c5]Glenn Fung:
The disputed federalist papers: SVM feature selection via concave minimization. Richard Tapia Celebration of Diversity in Computing Conference 2003: 42-46 - 2002
- [j1]Glenn Fung, Olvi L. Mangasarian, Alexander J. Smola:
Minimal Kernel Classifiers. J. Mach. Learn. Res. 3: 303-321 (2002) - [c4]Glenn Fung, Olvi L. Mangasarian, Jude W. Shavlik:
Knowledge-Based Support Vector Machine Classifiers. NIPS 2002: 521-528 - [c3]Glenn Fung, Olvi L. Mangasarian:
Incremental Support Vector Machine Classification. SDM 2002: 247-260 - 2001
- [c2]Glenn Fung, Olvi L. Mangasarian:
Proximal support vector machine classifiers. KDD 2001: 77-86 - 2000
- [c1]Glenn Fung, Olvi L. Mangasarian:
Data selection for support vector machine classifiers. KDD 2000: 64-70
Coauthor Index
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