Glenn Fung

92 papers A* 22A 8C 5Misc 2Journal 34Unranked 20
YearRankTypeTitle / Venue / Authors
2023 A* conf
Efficient Discrete Multi Marginal Optimal Transport Regularization.
ICLR
Ronak Mehta, Jeffery Kline, Vishnu Suresh Lokhande, Glenn Fung, Vikas Singh
2021 — conf
A Model for Zero-shot Text Multi-labeling Using Semantics-based Labels.
TransAI
Dan Dickinson, Ananth Raj GV, Glenn Fung
2021 J jnl
A Simple yet Brisk and Efficient Active Learning Platform for Text Classification.
CoRR
Teja Kanchinadam, Qian You, Keith Westpfahl, James Kim, Siva Gunda, Sebastian Seith, Glenn Fung
2021 J jnl
Deep Learning for Blocking in Entity Matching: A Design Space Exploration.
Proc. VLDB Endow.
Saravanan Thirumuruganathan, Han Li, Nan Tang, Mourad Ouzzani, Yash Govind, Derek Paulsen, Glenn Fung, AnHai Doan
2021 — conf
Document Classification and Information Extraction framework for Insurance Applications.
TransAI
Ananth Raj GV, Qian You, Daniel Dickinson, Eric Bunch, Glenn Fung
2021 J jnl
Domain Agnostic Few-Shot Learning For Document Intelligence.
CoRR
Jaya Krishna Mandivarapu, Eric Hunch, Glenn Fung
2021 J jnl
Editorial: Artificial Intelligence in Insurance and Finance.
Frontiers Appl. Math. Stat.
Glenn Fung, Luisa F. Polanía, Sou-Cheng T. Choi, Victor Wu, Lawrence Ma
2021 J jnl
Efficient Document Image Classification Using Region-Based Graph Neural Network.
CoRR
Jaya Krishna Mandivarapu, Eric Bunch, Qian You, Glenn Fung
2021 J jnl
Graph Neural Networks to Predict Customer Satisfaction Following Interactions with a Corporate Call Center.
CoRR
Teja Kanchinadam, Zihang Meng, Joseph Bockhorst, Vikas Singh, Glenn Fung
2021 — conf
Low Resource Quadratic Forms for Knowledge Graph Embeddings.
SustaiNLP@EMNLP
Zachary Zhou, Jeffery Kline, Devin Conathan, Glenn Fung
2021 J jnl
Nyströmformer: A Nyström-Based Algorithm for Approximating Self-Attention.
CoRR
Yunyang Xiong, Zhanpeng Zeng, Rudrasis Chakraborty, Mingxing Tan, Glenn Fung, Yin Li, Vikas Singh
2021 A* conf
Nyströmformer: A Nyström-based Algorithm for Approximating Self-Attention.
AAAI
Yunyang Xiong, Zhanpeng Zeng, Rudrasis Chakraborty, Mingxing Tan, Glenn Fung, Yin Li, Vikas Singh
2021 J jnl
Weighting vectors for machine learning: numerical harmonic analysis applied to boundary detection.
CoRR
Eric Bunch, Jeffery Kline, Daniel Dickinson, Suhaas Bhat, Glenn Fung
2021 J jnl
You Only Sample (Almost) Once: Linear Cost Self-Attention Via Bernoulli Sampling.
CoRR
Zhanpeng Zeng, Yunyang Xiong, Sathya N. Ravi, Shailesh Acharya, Glenn Fung, Vikas Singh
2020 J jnl
Designing and deploying insurance recommender systems using machine learning.
WIREs Data Mining Knowl. Discov.
Maleeha Qazi, Kaya Tollas, Teja Kanchinadam, Joseph Bockhorst, Glenn Fung
2020 — conf
Human-In-The-Loop Topic Discovery with Embedded Text Representations.
DaSH@KDD
Eric Bunch, Qian You, Glenn Fung
2020 J jnl
Practical applications of metric space magnitude and weighting vectors.
CoRR
Eric Bunch, Daniel Dickinson, Jeffery Kline, Glenn Fung
2020 — conf
Rationale-based Human-in-the-Loop via Supervised Attention.
DaSH@KDD
Teja Kanchinadam, Keith Westpfahl, Qian You, Glenn Fung
2020 J jnl
SGD Distributional Dynamics of Three Layer Neural Networks.
CoRR
Victor Luo, Yazhen Wang, Glenn Fung
2020 — conf
Using Optimal Embeddings to Learn New Intents with Few Examples: An Application in the Insurance Domain.
Converse@KDD
Shailesh Acharya, Glenn Fung
2019 A* conf
Discovering Temporal Patterns from Insurance Interaction Data.
AAAI
Maleeha Qazi, Srinivas Tunuguntla, Peng Lee, Teja Kanchinadam, Glenn Fung, Neeraj Arora
2019 J jnl
Mileage Extraction From Odometer Pictures for Automating Auto Insurance Processes.
Frontiers Appl. Math. Stat.
Shailesh Acharya, Glenn Fung
2019 A conf
Ordinal Regression Using Noisy Pairwise Comparisons for Body Mass Index Range Estimation.
WACV
Luisa F. Polanía, Glenn Fung, Dongning Wang
2019 J jnl
Task-Optimized Word Embeddings for Text Classification Representations.
Frontiers Appl. Math. Stat.
Sukrat Gupta, Teja Kanchinadam, Devin Conathan, Glenn Fung
2018 J jnl
CloudMatcher: A Hands-Off Cloud/Crowd Service for Entity Matching.
Proc. VLDB Endow.
Yash Govind, Erik Paulson, Palaniappan Nagarajan, Paul Suganthan G. C., AnHai Doan, Youngchoon Park, Glenn Fung, Devin Conathan, Marshall Carter, Mingju Sun
2018 — conf
Efficient Relative Attribute Learning Using Graph Neural Networks.
ECCV (14)
Zihang Meng, Nagesh Adluru, Hyunwoo J. Kim, Glenn Fung, Vikas Singh
2018 J jnl
Ordinal Regression using Noisy Pairwise Comparisons for Body Mass Index Range Estimation.
CoRR
Luisa F. Polanía, Dongning Wang, Glenn Fung
2018 C conf
Using Discriminative Graphical Models for Insurance Recommender Systems.
ICMLA
Teja Kanchinadam, Maleeha Qazi, Joseph Bockhorst, Mary Y. Morell, Katie J. Meissner, Glenn Fung
2017 — conf
Predicting Self-reported Customer Satisfaction of Interactions with a Corporate Call Center.
ECML/PKDD (3)
Joseph Bockhorst, Shi Yu, Luisa F. Polanía, Glenn Fung
2016 J jnl
Evaluating Crowdsourcing Participants in the Absence of Ground-Truth.
CoRR
Ramanathan Subramanian, Rómer Rosales, Glenn Fung, Jennifer G. Dy
2016 J jnl
Unsupervised and Semisupervised Classification Via Absolute Value Inequalities.
J. Optim. Theory Appl.
Glenn Fung, Olvi L. Mangasarian
2016 C conf
Using Temporal Discovery and Data-Driven Journey-Maps to Predict Customer Satisfaction.
ICMLA
Joe Bockhorst, Yingjian Wang, Sukrat Gupta, Maleeha Qazi, Mingju Sun, Glenn Fung
2015 J jnl
Predicting readmission risk with institution-specific prediction models.
Artif. Intell. Medicine
Shipeng Yu, Faisal Farooq, Alexander Van Esbroeck, Glenn Fung, Vikram Anand, Balaji Krishnapuram
2014 — conf
Active learning from uncertain crowd annotations.
Allerton
Yan Yan, Rómer Rosales, Glenn Fung, Jennifer G. Dy
2014 J jnl
Learning from multiple annotators with varying expertise.
Mach. Learn.
Yan Yan, Rómer Rosales, Glenn Fung, Subramanian Ramanathan, Jennifer G. Dy
2013 — conf
Predicting Readmission Risk with Institution Specific Prediction Models.
ICHI
Shipeng Yu, Alexander Van Esbroeck, Faisal Farooq, Glenn Fung, Vikram Anand, Balaji Krishnapuram
2013 J jnl
Privacy-preserving linear and nonlinear approximation via linear programming.
Optim. Methods Softw.
Glenn Fung, Olvi L. Mangasarian
2012 A conf
Active Learning from Multiple Knowledge Sources.
AISTATS
Yan Yan, Rómer Rosales, Glenn Fung, Faisal Farooq, Bharat Rao, Jennifer G. Dy
2012 Misc conf
Building Hospital-Specific Readmission Risk Prediction Models for Heart Failure, Acute Myocardial Infarction and Pneumonia patients.
AMIA
Shipeng Yu, Faisal Farooq, Glenn Fung, Balaji Krishnapuram, Alexander Van Esbroeck, Vikram Anand
2012 J jnl
Modeling Multiple Annotator Expertise in the Semi-Supervised Learning Scenario
CoRR
Yan Yan, Rómer Rosales, Glenn Fung, Jennifer G. Dy
2011 A* conf
Active Learning from Crowds.
ICML
Yan Yan, Rómer Rosales, Glenn Fung, Jennifer G. Dy
2011 J jnl
Equivalence of Minimal
J. Optim. Theory Appl.
Glenn Fung, O. L. Mangasarian
2010 A conf
Convex Principal Feature Selection.
SDM
Mahdokht Masaeli, Yan Yan, Ying Cui, Glenn Fung, Jennifer G. Dy
2010 A* conf
From Transformation-Based Dimensionality Reduction to Feature Selection.
ICML
Mahdokht Masaeli, Glenn Fung, Jennifer G. Dy
2010 A* conf
Medical coding classification by leveraging inter-code relationships.
KDD
Yan Yan, Glenn Fung, Jennifer G. Dy, Rómer Rosales
2010 A conf
Modeling Multiple Annotator Expertise in the Semi-Supervised Learning Scenario.
UAI
Yan Yan, Rómer Rosales, Glenn Fung, Jennifer G. Dy
2010 A conf
Modeling annotator expertise: Learning when everybody knows a bit of something.
AISTATS
Yan Yan, Rómer Rosales, Glenn Fung, Mark Schmidt, Gerardo Hermosillo Valadez, Luca Bogoni, Linda Moy, Jennifer G. Dy
2009 A* conf
Multi-Class Classifiers and their Underlying Shared Structure.
IJCAI
Volkan Vural, Glenn Fung, Rómer Rosales, Jennifer G. Dy
2009 J jnl
Proximal Knowledge-based Classification.
Stat. Anal. Data Min.
Olvi L. Mangasarian, Edward W. Wild, Glenn Fung
2009 C conf
Survival Prediction in Lung Cancer Treated with Radiotherapy: Bayesian Networks vs. Support Vector Machines in Handling Missing Data.
ICMLA
Andre Dekker, Cary Dehing-Oberije, Dirk De Ruysscher, Philippe Lambin, Kartik Komati, Glenn Fung, Shipeng Yu, Andrew Hope, Wilfried De Neve, Yolande Lievens
2009 J jnl
Using Local Dependencies within Batches to Improve Large Margin Classifiers.
J. Mach. Learn. Res.
Volkan Vural, Glenn Fung, Balaji Krishnapuram, Jennifer G. Dy, R. Bharat Rao
2008 — conf
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
Isaac Leichter, Richard Lederman, Eli Ratner, Nicolas Merlet, Glenn Fung, Balaji Krishnapuram, Philippe Bamberger
2008 J jnl
Fast semi-supervised SVM classifiers using
Optim. Methods Softw.
Volkan Vural, Glenn Fung, Jennifer G. Dy, Bharat Rao
2008 A* conf
Learning Sparse Kernels from 3D Surfaces for Heart Wall Motion Abnormality Detection.
AAAI
Glenn Fung, Sriram Krishnan, R. Bharat Rao, Hui Chen
2008 J jnl
Multiple-Instance Learning Algorithms for Computer-Aided Detection.
IEEE Trans. Biomed. Eng.
Murat Dundar, Glenn Fung, Balaji Krishnapuram, R. Bharat Rao
2008 A conf
On the Dangers of Cross-Validation. An Experimental Evaluation.
SDM
R. Bharat Rao, Glenn Fung
2008 — conf
Optimizing the CAD Process for Detecting Mammographic Lesions by a New Generation Algorithm Using Linear Classifiers and a Gradient Based Approach.
Digital Mammography / IWDM
Philippe Bamberger, Isaac Leichter, Nicolas Merlet, Eli Ratner, Glenn Fung, Richard Lederman
2008 J jnl
Privacy-preserving classification of vertically partitioned data via random kernels.
ACM Trans. Knowl. Discov. Data
Olvi L. Mangasarian, Edward W. Wild, Glenn Fung
2008 A* conf
Privacy-preserving cox regression for survival analysis.
KDD
Shipeng Yu, Glenn Fung, Rómer Rosales, Sriram Krishnan, R. Bharat Rao, Cary Dehing-Oberije, Philippe Lambin
2008 — ch.
Rule Extraction from Linear Support Vector Machines via Mathematical Programming.
Rule Extraction from Support Vector Machines
Glenn Fung, Sathyakama Sandilya, R. Bharat Rao
2008 A* conf
Structure learning in random fields for heart motion abnormality detection.
CVPR
Mark Schmidt, Kevin P. Murphy, Glenn Fung, Rómer Rosales
2007 A* conf
Automated Heart Wall Motion Abnormality Detection from Ultrasound Images Using Bayesian Networks.
IJCAI
Maleeha Qazi, Glenn Fung, Sriram Krishnan, Rómer Rosales, Harald Steck, R. Bharat Rao, Don Poldermans, Dhanalakshmi Chandrasekaran
2007 — conf
Fast Optimization Methods for L1 Regularization: A Comparative Study and Two New Approaches.
ECML
Mark Schmidt, Glenn Fung, Rómer Rosales
2007 A* conf
Feature Selection and Kernel Design via Linear Programming.
IJCAI
Glenn Fung, Rómer Rosales, R. Bharat Rao
2007 A* conf
LungCAD: a clinically approved, machine learning system for lung cancer detection.
KDD
R. Bharat Rao, Jinbo Bi, Glenn Fung, Marcos Salganicoff, Nancy Obuchowski, David P. Naidich
2007 C conf
Reducing a Biomarkers List via Mathematical Programming: Application to Gene Signatures to Detect Time-Dependent Hypoxia in Cancer.
ICMLA
Glenn Fung, Renaud Seigneuric, Sriram Krishnan, R. Bharat Rao, Brad G. Wouters, Philippe Lambin
2007 J jnl
SVM feature selection for classification of SPECT images of Alzheimer's disease using spatial information.
Knowl. Inf. Syst.
Glenn Fung, Jonathan Stoeckel
2006 — conf
Addressing Image Variability While Learning Classifiers for Detecting Clusters of Micro-calcifications.
Digital Mammography / IWDM
Glenn Fung, Balaji Krishnapuram, Nicolas Merlet, Eli Ratner, Philippe Bamberger, Jonathan Stoeckel, R. Bharat Rao
2006 — conf
Batch Classification with Applications in Computer Aided Diagnosis.
ECML
Volkan Vural, Glenn Fung, Balaji Krishnapuram, Jennifer G. Dy, R. Bharat Rao
2006 J jnl
Breast Tumor Susceptibility to Chemotherapy Via Support Vector Machines.
Comput. Manag. Sci.
Glenn Fung, O. L. Mangasarian
2006 A* conf
Computer aided detection via asymmetric cascade of sparse hyperplane classifiers.
KDD
Jinbo Bi, Senthil Periaswamy, Kazunori Okada, Toshiro Kubota, Glenn Fung, Marcos Salganicoff, R. Bharat Rao
2006 A* conf
Learning sparse metrics via linear programming.
KDD
Rómer Rosales, Glenn Fung
2006 — conf
Multiple Instance Learning for Computer Aided Diagnosis.
NIPS
Glenn Fung, Murat Dundar, Balaji Krishnapuram, R. Bharat Rao
2005 — conf
Learning Rankings via Convex Hull Separation.
NIPS
Glenn Fung, Rómer Rosales, Balaji Krishnapuram
2005 J jnl
Multicategory Proximal Support Vector Machine Classifiers.
Mach. Learn.
Glenn Fung, Olvi L. Mangasarian
2005 A* conf
Rule extraction from linear support vector machines.
KDD
Glenn Fung, Sathyakama Sandilya, R. Bharat Rao
2005 A* conf
SVM Feature Selection for Classification of SPECT Images of Alzheimer's Disease Using Spatial Information.
ICDM
Jonathan Stoeckel, Glenn Fung
2005 A* conf
Semi-Supervised Mixture of Kernels via LPBoost Methods.
ICDM
Jinbo Bi, Glenn Fung, Murat Dundar, R. Bharat Rao
2005 A conf
Sparse Fisher Discriminant Analysis for Computer Aided Detection.
SDM
Murat Dundar, Glenn Fung, Jinbo Bi, Sathyakama Sandilya, R. Bharat Rao
2005 C conf
Sparse classifiers for Automated HeartWall Motion Abnormality Detection.
ICMLA
Glenn Fung, Maleeha Qazi, Sriram Krishnan, Jinbo Bi, R. Bharat Rao, A. Katz
2004 J jnl
A Feature Selection Newton Method for Support Vector Machine Classification.
Comput. Optim. Appl.
Glenn Fung, O. L. Mangasarian
2004 A* conf
A fast iterative algorithm for fisher discriminant using heterogeneous kernels.
ICML
Glenn Fung, Murat Dundar, Jinbo Bi, R. Bharat Rao
2004 — conf
A methodology for training and validating a CAD system and potential pitfalls.
CARS
Murat Dundar, Glenn Fung, Luca Bogoni, Michael Macari, A. Megibow, R. Bharat Rao
2004 — conf
CAD for polyp detection: an invaluable tool to meet the increasing need for colon-cancer screening.
CARS
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
2003 J jnl
Finite Newton method for Lagrangian support vector machine classification.
Neurocomputing
Glenn Fung, Olvi L. Mangasarian
2003 A* conf
Knowledge-Based Nonlinear Kernel Classifiers.
COLT
Glenn Fung, Olvi L. Mangasarian, Jude W. Shavlik
2003 Misc conf
The disputed federalist papers: SVM feature selection via concave minimization.
Richard Tapia Celebration of Diversity in Computing Conference
Glenn Fung
2002 A conf
Incremental Support Vector Machine Classification.
SDM
Glenn Fung, Olvi L. Mangasarian
2002 — conf
Knowledge-Based Support Vector Machine Classifiers.
NIPS
Glenn Fung, Olvi L. Mangasarian, Jude W. Shavlik
2002 J jnl
Minimal Kernel Classifiers.
J. Mach. Learn. Res.
Glenn Fung, Olvi L. Mangasarian, Alexander J. Smola
2001 A* conf
Proximal support vector machine classifiers.
KDD
Glenn Fung, Olvi L. Mangasarian
2000 A* conf
Data selection for support vector machine classifiers.
KDD
Glenn Fung, Olvi L. Mangasarian