Data selection for support vector machine classifiers. - Glenn Fung; Olvi L. Mangasarian (KDD, 2000)

Proximal support vector machine classifiers. - Glenn Fung; Olvi L. Mangasarian (KDD, 2001)

Knowledge-Based Support Vector Machine Classifiers. - Glenn Fung; Olvi L. Mangasarian; Jude W. Shavlik (NIPS, 2002)

Incremental Support Vector Machine Classification. - Glenn Fung; Olvi L. Mangasarian (SDM, 2002)

Minimal Kernel Classifiers. - Glenn Fung; Olvi L. Mangasarian; Alexander J. Smola (J. Mach. Learn. Res., 2002)

Knowledge-Based Nonlinear Kernel Classifiers. - Glenn Fung; Olvi L. Mangasarian; Jude W. Shavlik (COLT, 2003)

The disputed federalist papers: SVM feature selection via concave minimization. - Glenn Fung (Richard Tapia Celebration of Diversity in Computing Conference, 2003)

Finite Newton method for Lagrangian support vector machine classification. - Glenn Fung; Olvi L. Mangasarian (Neurocomputing, 2003)

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; et al. (CARS, 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 (CARS, 2004)

A fast iterative algorithm for fisher discriminant using heterogeneous kernels. - Glenn Fung; Murat Dundar; Jinbo Bi; R. Bharat Rao (ICML, 2004)

A Feature Selection Newton Method for Support Vector Machine Classification. - Glenn Fung; O. L. Mangasarian (Comput. Optim. Appl., 2004)

Semi-Supervised Mixture of Kernels via LPBoost Methods. - Jinbo Bi; Glenn Fung; Murat Dundar; R. Bharat Rao (ICDM, 2005)

Sparse classifiers for Automated HeartWall Motion Abnormality Detection. - Glenn Fung; Maleeha Qazi; Sriram Krishnan; Jinbo Bi; R. Bharat Rao; A. Katz (ICMLA, 2005)

Rule extraction from linear support vector machines. - Glenn Fung; Sathyakama Sandilya; R. Bharat Rao (KDD, 2005)

Learning Rankings via Convex Hull Separation. - Glenn Fung; Rómer Rosales; Balaji Krishnapuram (NIPS, 2005)

Sparse Fisher Discriminant Analysis for Computer Aided Detection. - Murat Dundar; Glenn Fung; Jinbo Bi; Sathyakama Sandilya; R. Bharat Rao (SDM, 2005)

Multicategory Proximal Support Vector Machine Classifiers. - Glenn Fung; Olvi L. Mangasarian (Mach. Learn., 2005)

Batch Classification with Applications in Computer Aided Diagnosis. - Volkan Vural; Glenn Fung; Balaji Krishnapuram; Jennifer G. Dy; R. Bharat Rao (ECML, 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 (KDD, 2006)

Learning sparse metrics via linear programming. - Rómer Rosales; Glenn Fung (KDD, 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 (Digital Mammography / IWDM, 2006)

Multiple Instance Learning for Computer Aided Diagnosis. - Glenn Fung; Murat Dundar; Balaji Krishnapuram; R. Bharat Rao (NIPS, 2006)

Breast Tumor Susceptibility to Chemotherapy Via Support Vector Machines. - Glenn Fung; O. L. Mangasarian (Comput. Manag. Sci., 2006)

Fast Optimization Methods for L1 Regularization: A Comparative Study and Two New Approaches. - Mark Schmidt 001; Glenn Fung; Rómer Rosales (ECML, 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 (ICMLA, 2007)

Feature Selection and Kernel Design via Linear Programming. - Glenn Fung; Rómer Rosales; R. Bharat Rao (IJCAI, 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 (IJCAI, 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 (KDD, 2007)

SVM feature selection for classification of SPECT images of Alzheimer's disease using spatial information. - Glenn Fung; Jonathan Stoeckel (Knowl. Inf. Syst., 2007)

Learning Sparse Kernels from 3D Surfaces for Heart Wall Motion Abnormality Detection. - Glenn Fung; Sriram Krishnan; R. Bharat Rao; Hui Chen (AAAI, 2008)

Structure learning in random fields for heart motion abnormality detection. - Mark Schmidt 001; Kevin P. Murphy; Glenn Fung; Rómer Rosales (CVPR, 2008)

Privacy-preserving cox regression for survival analysis. - Shipeng Yu; Glenn Fung; Rómer Rosales; Sriram Krishnan; R. Bharat Rao; Cary Dehing-Oberije; Philippe Lambin (KDD, 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 (Digital Mammography / IWDM, 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 (Digital Mammography / IWDM, 2008)

On the Dangers of Cross-Validation. An Experimental Evaluation. - R. Bharat Rao; Glenn Fung (SDM, 2008)

Fast semi-supervised SVM classifiers using a priori metric information. - Volkan Vural; Glenn Fung; Jennifer G. Dy; Bharat Rao (Optim. Methods Softw., 2008)

Multiple-Instance Learning Algorithms for Computer-Aided Detection. - Murat Dundar; Glenn Fung; Balaji Krishnapuram; R. Bharat Rao (IEEE Trans. Biomed. Eng., 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)

Rule Extraction from Linear Support Vector Machines via Mathematical Programming. - Glenn Fung; Sathyakama Sandilya; R. Bharat Rao (Rule Extraction from Support Vector Machines, 2008)

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 (ICMLA, 2009)

Multi-Class Classifiers and their Underlying Shared Structure. - Volkan Vural; Glenn Fung; Rómer Rosales; Jennifer G. Dy (IJCAI, 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)

Proximal Knowledge-based Classification. - Olvi L. Mangasarian; Edward W. Wild; Glenn Fung (Stat. Anal. Data Min., 2009)

From Transformation-Based Dimensionality Reduction to Feature Selection. - Mahdokht Masaeli; Glenn Fung; Jennifer G. Dy (ICML, 2010)

Medical coding classification by leveraging inter-code relationships. - Yan Yan 024; Glenn Fung; Jennifer G. Dy; Rómer Rosales (KDD, 2010)

Convex Principal Feature Selection. - Mahdokht Masaeli; Yan Yan 024; Ying Cui; Glenn Fung; Jennifer G. Dy (SDM, 2010)

Modeling Multiple Annotator Expertise in the Semi-Supervised Learning Scenario. - Yan Yan 024; Rómer Rosales; Glenn Fung; Jennifer G. Dy (UAI, 2010)

Modeling annotator expertise: Learning when everybody knows a bit of something. - Yan Yan 024; Rómer Rosales; Glenn Fung; Mark Schmidt 001; Gerardo Hermosillo Valadez; Luca Bogoni; Linda Moy; Jennifer G. Dy (AISTATS, 2010)

Active Learning from Crowds. - Yan Yan 024; Rómer Rosales; Glenn Fung; Jennifer G. Dy (ICML, 2011)

Equivalence of Minimal ℓ0- and ℓp-Norm Solutions of Linear Equalities, Inequalities and Linear Programs for Sufficiently Small p. - Glenn Fung; O. L. Mangasarian (J. Optim. Theory Appl., 2011)

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 (AMIA, 2012)

Active Learning from Multiple Knowledge Sources. - Yan Yan 024; Rómer Rosales; Glenn Fung; Faisal Farooq; Bharat Rao; Jennifer G. Dy (AISTATS, 2012)

Privacy-preserving linear and nonlinear approximation via linear programming. - Glenn Fung; Olvi L. Mangasarian (Optim. Methods Softw., 2013)

Active learning from uncertain crowd annotations. - Yan Yan 024; Rómer Rosales; Glenn Fung; Jennifer G. Dy (Allerton, 2014)

Learning from multiple annotators with varying expertise. - Yan Yan 024; Rómer Rosales; Glenn Fung; Subramanian Ramanathan; Jennifer G. Dy (Mach. Learn., 2014)

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)

Using Temporal Discovery and Data-Driven Journey-Maps to Predict Customer Satisfaction. - Joe Bockhorst; Yingjian Wang; Sukrat Gupta; Maleeha Qazi; Mingju Sun; Glenn Fung (ICMLA, 2016)

Evaluating Crowdsourcing Participants in the Absence of Ground-Truth. - Ramanathan Subramanian; Rómer Rosales; Glenn Fung; Jennifer G. Dy (CoRR, 2016)

Unsupervised and Semisupervised Classification Via Absolute Value Inequalities. - Glenn Fung; Olvi L. Mangasarian (J. Optim. Theory Appl., 2016)

Predicting Self-reported Customer Satisfaction of Interactions with a Corporate Call Center. - Joseph Bockhorst; Shi Yu; Luisa F. Polanía; Glenn Fung (ECML/PKDD (3), 2017)

An Insurance Recommendation System Using Bayesian Networks. - Maleeha Qazi; Glenn Moo Fung; Katie J. Meissner; Eduardo R. Fontes (RecSys, 2017)

Efficient Relative Attribute Learning Using Graph Neural Networks. - Zihang Meng; Nagesh Adluru; Hyunwoo J. Kim; Glenn Fung; Vikas Singh (ECCV (14), 2018)

Using Discriminative Graphical Models for Insurance Recommender Systems. - Teja Kanchinadam; Maleeha Qazi; Joseph Bockhorst; Mary Y. Morell; Katie J. Meissner; Glenn Fung (ICMLA, 2018)

CloudMatcher: A Hands-Off Cloud/Crowd Service for Entity Matching. - Yash Govind; Erik Paulson 001; Palaniappan Nagarajan; Paul Suganthan G. C.; AnHai Doan; Youngchoon Park; Glenn Fung; Devin Conathan; Marshall Carter; Mingju Sun (Proc. VLDB Endow., 2018)

Probabilistic-Logic Bots for Efficient Evaluation of Business Rules Using Conversational Interfaces. - Joseph Bockhorst; Devin Conathan; Glenn Moo Fung (AAAI, 2019)

Discovering Temporal Patterns from Insurance Interaction Data. - Maleeha Qazi; Srinivas Tunuguntla; Peng Lee; Teja Kanchinadam; Glenn Fung; Neeraj Arora (AAAI, 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; et al. (SIGMOD Conference, 2019)

Ordinal Regression Using Noisy Pairwise Comparisons for Body Mass Index Range Estimation. - Luisa F. Polanía; Glenn Fung; Dongning Wang (WACV, 2019)

Mileage Extraction From Odometer Pictures for Automating Auto Insurance Processes. - Shailesh Acharya; Glenn Fung (Frontiers Appl. Math. Stat., 2019)

Task-Optimized Word Embeddings for Text Classification Representations. - Sukrat Gupta; Teja Kanchinadam; Devin Conathan; Glenn Fung (Frontiers Appl. Math. Stat., 2019)

Optimizing Nondecomposable Data Dependent Regularizers via Lagrangian Reparameterization Offers Significant Performance and Efficiency Gains. - Sathya N. Ravi; Abhay Venkatesh; Glenn Moo Fung; Vikas Singh (AAAI, 2020)

Using Optimal Embeddings to Learn New Intents with Few Examples: An Application in the Insurance Domain. - Shailesh Acharya; Glenn Fung (Converse@KDD, 2020)

Human-In-The-Loop Topic Discovery with Embedded Text Representations. - Eric Bunch; Qian You; Glenn Fung (DaSH@KDD, 2020)

Rationale-based Human-in-the-Loop via Supervised Attention. - Teja Kanchinadam; Keith Westpfahl; Qian You; Glenn Fung (DaSH@KDD, 2020)

Practical applications of metric space magnitude and weighting vectors. - Eric Bunch; Daniel Dickinson; Jeffery Kline; Glenn Fung (CoRR, 2020)

SGD Distributional Dynamics of Three Layer Neural Networks. - Victor Luo; Yazhen Wang; Glenn Fung (CoRR, 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)

Nyströmformer: A Nyström-based Algorithm for Approximating Self-Attention. - Yunyang Xiong; Zhanpeng Zeng; Rudrasis Chakraborty; Mingxing Tan; Glenn Fung; Yin Li 003; Vikas Singh (AAAI, 2021)

Low Resource Quadratic Forms for Knowledge Graph Embeddings. - Zachary Zhou; Jeffery Kline; Devin Conathan; Glenn Fung (SustaiNLP@EMNLP, 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 (ICML, 2021)

A Model for Zero-shot Text Multi-labeling Using Semantics-based Labels. - Dan Dickinson; Ananth Raj GV; Glenn Fung (TransAI, 2021)

Document Classification and Information Extraction framework for Insurance Applications. - Ananth Raj GV; Qian You; Daniel Dickinson; Eric Bunch; Glenn Fung (TransAI, 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)

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)

Weighting vectors for machine learning: numerical harmonic analysis applied to boundary detection. - Eric Bunch; Jeffery Kline; Daniel Dickinson; Suhaas Bhat; 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)

Domain Agnostic Few-Shot Learning For Document Intelligence. - Jaya Krishna Mandivarapu; Eric Hunch; Glenn Fung (CoRR, 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)

Deep Learning for Blocking in Entity Matching: A Design Space Exploration. - Saravanan Thirumuruganathan; Han Li; Nan Tang 001; Mourad Ouzzani; Yash Govind; Derek Paulsen; Glenn Fung; AnHai Doan (Proc. VLDB Endow., 2021)

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 (AAAI, 2022)

Multi Resolution Analysis (MRA) for Approximate Self-Attention. - Zhanpeng Zeng; Sourav Pal; Jeffery Kline; Glenn Moo Fung; Vikas Singh (ICML, 2022)

Efficient Discrete Multi Marginal Optimal Transport Regularization. - Ronak Mehta; Jeffery Kline; Vishnu Suresh Lokhande; Glenn Fung; Vikas Singh (ICLR, 2023)

Linear programming with nonparametric penalty programs and iterated thresholding. - Jeffery Kline; Glenn Martin Fung (Optim. Methods Softw., 2023)