Glenn Fung

According to our database, Glenn Fung authored at least 94 papers between 2000 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Linear programming with nonparametric penalty programs and iterated thresholding.

Jeffery Kline, Glenn Martin Fung

Optim. Methods Softw., January, 2023

Efficient Discrete Multi Marginal Optimal Transport Regularization.

Ronak Mehta, Jeffery Kline, Vishnu Suresh Lokhande, Glenn Fung, Vikas Singh

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Multi Resolution Analysis (MRA) for Approximate Self-Attention.

Zhanpeng Zeng, Sourav Pal, Jeffery Kline, Glenn Moo Fung, Vikas Singh

Proceedings of the International Conference on Machine Learning, 2022

Harvest - a System for Creating Structured Rate Filing Data from Filing PDFs.

Ender Tekin, Qian You, Devin M. Conathan, Glenn Moo Fung, Thomas S. Kneubuehl

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Deep Learning for Blocking in Entity Matching: A Design Space Exploration.

Saravanan Thirumuruganathan, Han Li, Nan Tang, Mourad Ouzzani, Yash Govind, Derek Paulsen, Glenn Fung, AnHai Doan

Proc. VLDB Endow., 2021

Editorial: Artificial Intelligence in Insurance and Finance.

Glenn Fung, Luisa F. Polanía, Sou-Cheng T. Choi, Victor Wu, Lawrence Ma

Frontiers Appl. Math. Stat., 2021

Domain Agnostic Few-Shot Learning For Document Intelligence.

Jaya Krishna Mandivarapu, Eric Hunch, Glenn Fung

CoRR, 2021

Efficient Document Image Classification Using Region-Based Graph Neural Network.

Jaya Krishna Mandivarapu, Eric Bunch, Qian You, Glenn Fung

CoRR, 2021

Weighting vectors for machine learning: numerical harmonic analysis applied to boundary detection.

Eric Bunch, Jeffery Kline, Daniel Dickinson, Suhaas Bhat, Glenn Fung

CoRR, 2021

A Simple yet Brisk and Efficient Active Learning Platform for Text Classification.

Teja Kanchinadam, Qian You, Keith Westpfahl, James Kim, Siva Gunda, Sebastian Seith, Glenn Fung

CoRR, 2021

Graph Neural Networks to Predict Customer Satisfaction Following Interactions with a Corporate Call Center.

Teja Kanchinadam, Zihang Meng, Joseph Bockhorst, Vikas Singh, Glenn Fung

CoRR, 2021

Document Classification and Information Extraction framework for Insurance Applications.

Ananth Raj GV, Qian You, Daniel Dickinson, Eric Bunch, Glenn Fung

Proceedings of the Third International Conference on Transdisciplinary AI, 2021

A Model for Zero-shot Text Multi-labeling Using Semantics-based Labels.

Dan Dickinson, Ananth Raj GV, Glenn Fung

Proceedings of the Third International Conference on Transdisciplinary AI, 2021

You Only Sample (Almost) Once: Linear Cost Self-Attention Via Bernoulli Sampling.

Zhanpeng Zeng, Yunyang Xiong, Sathya N. Ravi, Shailesh Acharya, Glenn Moo Fung, Vikas Singh

Proceedings of the 38th International Conference on Machine Learning, 2021

Low Resource Quadratic Forms for Knowledge Graph Embeddings.

Zachary Zhou, Jeffery Kline, Devin Conathan, Glenn Fung

Proceedings of the Second Workshop on Simple and Efficient Natural Language Processing, 2021

Nyströmformer: A Nyström-based Algorithm for Approximating Self-Attention.

Yunyang Xiong, Zhanpeng Zeng, Rudrasis Chakraborty, Mingxing Tan, Glenn Fung, Yin Li, Vikas Singh

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Designing and deploying insurance recommender systems using machine learning.

Maleeha Qazi, Kaya Tollas, Teja Kanchinadam, Joseph Bockhorst, Glenn Fung

WIREs Data Mining Knowl. Discov., 2020

SGD Distributional Dynamics of Three Layer Neural Networks.

Victor Luo, Yazhen Wang, Glenn Fung

CoRR, 2020

Practical applications of metric space magnitude and weighting vectors.

Eric Bunch, Daniel Dickinson, Jeffery Kline, Glenn Fung

CoRR, 2020

Rationale-based Human-in-the-Loop via Supervised Attention.

Teja Kanchinadam, Keith Westpfahl, Qian You, Glenn Fung

Proceedings of the 1st Workshop on Data Science with Human in the Loop, 2020

Human-In-The-Loop Topic Discovery with Embedded Text Representations.

Eric Bunch, Qian You, Glenn Fung

Proceedings of the 1st Workshop on Data Science with Human in the Loop, 2020

Using Optimal Embeddings to Learn New Intents with Few Examples: An Application in the Insurance Domain.

Shailesh Acharya, Glenn Fung

Proceedings of the KDD 2020 Workshop on Conversational Systems Towards Mainstream Adoption co-located with the 26TH ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD 2020), 2020

Optimizing Nondecomposable Data Dependent Regularizers via Lagrangian Reparameterization Offers Significant Performance and Efficiency Gains.

Sathya N. Ravi, Abhay Venkatesh, Glenn Moo Fung, Vikas Singh

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Task-Optimized Word Embeddings for Text Classification Representations.

Sukrat Gupta, Teja Kanchinadam, Devin Conathan, Glenn Fung

Frontiers Appl. Math. Stat., 2019

Mileage Extraction From Odometer Pictures for Automating Auto Insurance Processes.

Shailesh Acharya, Glenn Fung

Frontiers Appl. Math. Stat., 2019

Ordinal Regression Using Noisy Pairwise Comparisons for Body Mass Index Range Estimation.

Luisa F. Polanía, Glenn Fung, Dongning Wang

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2019

Entity Matching Meets Data Science: A Progress Report from the Magellan Project.

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

Proceedings of the 2019 International Conference on Management of Data, 2019

Discovering Temporal Patterns from Insurance Interaction Data.

Maleeha Qazi, Srinivas Tunuguntla, Peng Lee, Teja Kanchinadam, Glenn Fung, Neeraj Arora

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

Probabilistic-Logic Bots for Efficient Evaluation of Business Rules Using Conversational Interfaces.

Joseph Bockhorst, Devin Conathan, Glenn Moo Fung

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

CloudMatcher: A Hands-Off Cloud/Crowd Service for Entity Matching.

Yash Govind, Erik Paulson, Palaniappan Nagarajan, Paul Suganthan G. C., AnHai Doan, Youngchoon Park, Glenn Fung, Devin Conathan, Marshall Carter, Mingju Sun

Proc. VLDB Endow., 2018

Using Discriminative Graphical Models for Insurance Recommender Systems.

Teja Kanchinadam, Maleeha Qazi, Joseph Bockhorst, Mary Y. Morell, Katie J. Meissner, Glenn Fung

Proceedings of the 17th IEEE International Conference on Machine Learning and Applications, 2018

Efficient Relative Attribute Learning Using Graph Neural Networks.

Zihang Meng, Nagesh Adluru, Hyunwoo J. Kim, Glenn Fung, Vikas Singh

Proceedings of the Computer Vision - ECCV 2018, 2018

2017

An Insurance Recommendation System Using Bayesian Networks.

Maleeha Qazi, Glenn Moo Fung, Katie J. Meissner, Eduardo R. Fontes

Proceedings of the Eleventh ACM Conference on Recommender Systems, 2017

Predicting Self-reported Customer Satisfaction of Interactions with a Corporate Call Center.

Joseph Bockhorst, Shi Yu, Luisa F. Polanía, Glenn Fung

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

2016

Unsupervised and Semisupervised Classification Via Absolute Value Inequalities.

Glenn Fung, Olvi L. Mangasarian

J. Optim. Theory Appl., 2016

Evaluating Crowdsourcing Participants in the Absence of Ground-Truth.

Ramanathan Subramanian, Rómer Rosales, Glenn Fung, Jennifer G. Dy

CoRR, 2016

Using Temporal Discovery and Data-Driven Journey-Maps to Predict Customer Satisfaction.

Joe Bockhorst, Yingjian Wang, Sukrat Gupta, Maleeha Qazi, Mingju Sun, Glenn Fung

Proceedings of the 15th IEEE International Conference on Machine Learning and Applications, 2016

2015

Predicting readmission risk with institution-specific prediction models.

Shipeng Yu, Faisal Farooq, Alexander Van Esbroeck, Glenn Fung, Vikram Anand, Balaji Krishnapuram

Artif. Intell. Medicine, 2015

2014

Learning from multiple annotators with varying expertise.

Yan Yan, Rómer Rosales, Glenn Fung, Subramanian Ramanathan, Jennifer G. Dy

Mach. Learn., 2014

Active learning from uncertain crowd annotations.

Yan Yan, Rómer Rosales, Glenn Fung, Jennifer G. Dy

Proceedings of the 52nd Annual Allerton Conference on Communication, 2014

2013

Privacy-preserving linear and nonlinear approximation via linear programming.

Glenn Fung, Olvi L. Mangasarian

Optim. Methods Softw., 2013

2012

Active Learning from Multiple Knowledge Sources.

Yan Yan, Rómer Rosales, Glenn Fung, Faisal Farooq, Bharat Rao, Jennifer G. Dy

Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Building Hospital-Specific Readmission Risk Prediction Models for Heart Failure, Acute Myocardial Infarction and Pneumonia patients.

Shipeng Yu, Faisal Farooq, Glenn Fung, Balaji Krishnapuram, Alexander Van Esbroeck, Vikram Anand

Proceedings of the AMIA 2012, 2012

2011

Equivalence of Minimal <i>ℓ</i>₀- and <i>ℓ</i>_<i>p</i>-Norm Solutions of Linear Equalities, Inequalities and Linear Programs for Sufficiently Small <i>p</i>.

Glenn Fung, O. L. Mangasarian

J. Optim. Theory Appl., 2011

Active Learning from Crowds.

Yan Yan, Rómer Rosales, Glenn Fung, Jennifer G. Dy

Proceedings of the 28th International Conference on Machine Learning, 2011

2010

Modeling annotator expertise: Learning when everybody knows a bit of something.

Yan Yan, Rómer Rosales, Glenn Fung, Mark Schmidt, Gerardo Hermosillo Valadez, Luca Bogoni, Linda Moy, Jennifer G. Dy

Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Modeling Multiple Annotator Expertise in the Semi-Supervised Learning Scenario.

Yan Yan, Rómer Rosales, Glenn Fung, Jennifer G. Dy

Proceedings of the UAI 2010, 2010

Convex Principal Feature Selection.

Mahdokht Masaeli, Yan Yan, Ying Cui, Glenn Fung, Jennifer G. Dy

Proceedings of the SIAM International Conference on Data Mining, 2010

Medical coding classification by leveraging inter-code relationships.

Yan Yan, Glenn Fung, Jennifer G. Dy, Rómer Rosales

Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2010

From Transformation-Based Dimensionality Reduction to Feature Selection.

Mahdokht Masaeli, Glenn Fung, Jennifer G. Dy

Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

2009

Proximal Knowledge-based Classification.

Olvi L. Mangasarian, Edward W. Wild, Glenn Fung

Stat. Anal. Data Min., 2009

Using Local Dependencies within Batches to Improve Large Margin Classifiers.

Volkan Vural, Glenn Fung, Balaji Krishnapuram, Jennifer G. Dy, R. Bharat Rao

J. Mach. Learn. Res., 2009

Multi-Class Classifiers and their Underlying Shared Structure.

Volkan Vural, Glenn Fung, Rómer Rosales, Jennifer G. Dy

Proceedings of the IJCAI 2009, 2009

Survival Prediction in Lung Cancer Treated with Radiotherapy: Bayesian Networks vs. Support Vector Machines in Handling Missing Data.

Andre Dekker, Cary Dehing-Oberije, Dirk De Ruysscher, Philippe Lambin, Kartik Komati, Glenn Fung, Shipeng Yu, Andrew Hope, Wilfried De Neve, Yolande Lievens

Proceedings of the International Conference on Machine Learning and Applications, 2009

2008

Rule Extraction from Linear Support Vector Machines via Mathematical Programming.

Glenn Fung, Sathyakama Sandilya, R. Bharat Rao

Proceedings of the Rule Extraction from Support Vector Machines, 2008

Privacy-preserving classification of vertically partitioned data via random kernels.

Olvi L. Mangasarian, Edward W. Wild, Glenn Fung

ACM Trans. Knowl. Discov. Data, 2008

Multiple-Instance Learning Algorithms for Computer-Aided Detection.

Murat Dundar, Glenn Fung, Balaji Krishnapuram, R. Bharat Rao

IEEE Trans. Biomed. Eng., 2008

Fast semi-supervised SVM classifiers using <i>a priori</i> metric information.

Volkan Vural, Glenn Fung, Jennifer G. Dy, Bharat Rao

Optim. Methods Softw., 2008

On the Dangers of Cross-Validation. An Experimental Evaluation.

R. Bharat Rao, Glenn Fung

Proceedings of the SIAM International Conference on Data Mining, 2008

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?.

Isaac Leichter, Richard Lederman, Eli Ratner, Nicolas Merlet, Glenn Fung, Balaji Krishnapuram, Philippe Bamberger

Proceedings of the Digital Mammography, 2008

Optimizing the CAD Process for Detecting Mammographic Lesions by a New Generation Algorithm Using Linear Classifiers and a Gradient Based Approach.

Philippe Bamberger, Isaac Leichter, Nicolas Merlet, Eli Ratner, Glenn Fung, Richard Lederman

Proceedings of the Digital Mammography, 2008

Privacy-preserving cox regression for survival analysis.

Shipeng Yu, Glenn Fung, Rómer Rosales, Sriram Krishnan, R. Bharat Rao, Cary Dehing-Oberije, Philippe Lambin

Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2008

Structure learning in random fields for heart motion abnormality detection.

Mark Schmidt, Kevin P. Murphy, Glenn Fung, Rómer Rosales

Proceedings of the 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2008), 2008

Learning Sparse Kernels from 3D Surfaces for Heart Wall Motion Abnormality Detection.

Glenn Fung, Sriram Krishnan, R. Bharat Rao, Hui Chen

Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence, 2008

2007

SVM feature selection for classification of SPECT images of Alzheimer's disease using spatial information.

Glenn Fung, Jonathan Stoeckel

Knowl. Inf. Syst., 2007

LungCAD: a clinically approved, machine learning system for lung cancer detection.

R. Bharat Rao, Jinbo Bi, Glenn Fung, Marcos Salganicoff, Nancy Obuchowski, David P. Naidich

Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2007

Automated Heart Wall Motion Abnormality Detection from Ultrasound Images Using Bayesian Networks.

Maleeha Qazi, Glenn Fung, Sriram Krishnan, Rómer Rosales, Harald Steck, R. Bharat Rao, Don Poldermans, Dhanalakshmi Chandrasekaran

Proceedings of the IJCAI 2007, 2007

Feature Selection and Kernel Design via Linear Programming.

Glenn Fung, Rómer Rosales, R. Bharat Rao

Proceedings of the IJCAI 2007, 2007

Reducing a Biomarkers List via Mathematical Programming: Application to Gene Signatures to Detect Time-Dependent Hypoxia in Cancer.

Glenn Fung, Renaud Seigneuric, Sriram Krishnan, R. Bharat Rao, Brad G. Wouters, Philippe Lambin

Proceedings of the Sixth International Conference on Machine Learning and Applications, 2007

Fast Optimization Methods for L1 Regularization: A Comparative Study and Two New Approaches.

Mark Schmidt, Glenn Fung, Rómer Rosales

Proceedings of the Machine Learning: ECML 2007, 2007

2006

Breast Tumor Susceptibility to Chemotherapy Via Support Vector Machines.

Glenn Fung, O. L. Mangasarian

Comput. Manag. Sci., 2006

Multiple Instance Learning for Computer Aided Diagnosis.

Glenn Fung, Murat Dundar, Balaji Krishnapuram, R. Bharat Rao

Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Addressing Image Variability While Learning Classifiers for Detecting Clusters of Micro-calcifications.

Glenn Fung, Balaji Krishnapuram, Nicolas Merlet, Eli Ratner, Philippe Bamberger, Jonathan Stoeckel, R. Bharat Rao

Proceedings of the Digital Mammography, 2006

Learning sparse metrics via linear programming.

Rómer Rosales, Glenn Fung

Proceedings of the Twelfth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2006

Computer aided detection via asymmetric cascade of sparse hyperplane classifiers.

Jinbo Bi, Senthil Periaswamy, Kazunori Okada, Toshiro Kubota, Glenn Fung, Marcos Salganicoff, R. Bharat Rao

Proceedings of the Twelfth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2006

Batch Classification with Applications in Computer Aided Diagnosis.

Volkan Vural, Glenn Fung, Balaji Krishnapuram, Jennifer G. Dy, R. Bharat Rao

Proceedings of the Machine Learning: ECML 2006, 2006

2005

Multicategory Proximal Support Vector Machine Classifiers.

Glenn Fung, Olvi L. Mangasarian

Mach. Learn., 2005

Sparse Fisher Discriminant Analysis for Computer Aided Detection.

Murat Dundar, Glenn Fung, Jinbo Bi, Sathyakama Sandilya, R. Bharat Rao

Proceedings of the 2005 SIAM International Conference on Data Mining, 2005

Learning Rankings via Convex Hull Separation.

Glenn Fung, Rómer Rosales, Balaji Krishnapuram

Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

Rule extraction from linear support vector machines.

Glenn Fung, Sathyakama Sandilya, R. Bharat Rao

Proceedings of the Eleventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2005

Sparse classifiers for Automated HeartWall Motion Abnormality Detection.

Glenn Fung, Maleeha Qazi, Sriram Krishnan, Jinbo Bi, R. Bharat Rao, A. Katz

Proceedings of the Fourth International Conference on Machine Learning and Applications, 2005

Semi-Supervised Mixture of Kernels via LPBoost Methods.

Jinbo Bi, Glenn Fung, Murat Dundar, R. Bharat Rao

Proceedings of the 5th IEEE International Conference on Data Mining (ICDM 2005), 2005

2004

A Feature Selection Newton Method for Support Vector Machine Classification.

Glenn Fung, O. L. Mangasarian

Comput. Optim. Appl., 2004

A fast iterative algorithm for fisher discriminant using heterogeneous kernels.

Glenn Fung, Murat Dundar, Jinbo Bi, R. Bharat Rao

Proceedings of the Machine Learning, 2004

A methodology for training and validating a CAD system and potential pitfalls.

Murat Dundar, Glenn Fung, Luca Bogoni, Michael Macari, A. Megibow, R. Bharat Rao

Proceedings of the CARS 2004. Computer Assisted Radiology and Surgery. Proceedings of the 18th International Congress and Exhibition, 2004

CAD for polyp detection: an invaluable tool to meet the increasing need for colon-cancer screening.

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

Proceedings of the CARS 2004. Computer Assisted Radiology and Surgery. Proceedings of the 18th International Congress and Exhibition, 2004

2003

Finite Newton method for Lagrangian support vector machine classification.

Glenn Fung, Olvi L. Mangasarian

Neurocomputing, 2003

The disputed federalist papers: SVM feature selection via concave minimization.

Glenn Fung

Proceedings of the Richard Tapia Celebration of Diversity in Computing Conference 2003, 2003

Knowledge-Based Nonlinear Kernel Classifiers.

Glenn Fung, Olvi L. Mangasarian, Jude W. Shavlik

Proceedings of the Computational Learning Theory and Kernel Machines, 2003

2002

Minimal Kernel Classifiers.

Glenn Fung, Olvi L. Mangasarian, Alexander J. Smola

J. Mach. Learn. Res., 2002

Incremental Support Vector Machine Classification.

Glenn Fung, Olvi L. Mangasarian

Proceedings of the Second SIAM International Conference on Data Mining, 2002

Knowledge-Based Support Vector Machine Classifiers.

Glenn Fung, Olvi L. Mangasarian, Jude W. Shavlik

Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

2001

Proximal support vector machine classifiers.

Glenn Fung, Olvi L. Mangasarian

Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining, 2001

2000

Data selection for support vector machine classifiers.

Glenn Fung, Olvi L. Mangasarian

Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining, 2000