Glenn Fung

Glenn Fung, Balaji Krishnapuram, Philippe Lambin, 2007, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

Modeling Multiple Annotator Expertise in the Semi-Supervised Learning Scenario

Jennifer G. Dy, Glenn Fung, Rómer Rosales, 2010, UAI.

A Simple but Highly Effective Approach to Evaluate the Prognostic Performance of Gene Expression Signatures

Glenn Fung, Harald Steck, Philippe Lambin, 2011, PloS one.

From Transformation-Based Dimensionality Reduction to Feature Selection

Jennifer G. Dy, Glenn Fung, Mahdokht Masaeli, 2010, ICML.

Multi-Class Classifiers and their Underlying Shared Structure

Jennifer G. Dy, Rómer Rosales, Glenn Fung, 2009, IJCAI.

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

Glenn Fung, Rómer Rosales, R. Bharat Rao, 2007, IJCAI.

A new, accurate predictive model for incident hypertension

Glenn Fung, Uwe Völker, Shipeng Yu, 2013, Journal of hypertension.

Active learning from uncertain crowd annotations

Jennifer G. Dy, Glenn Fung, Rómer Rosales, 2014, 2014 52nd Annual Allerton Conference on Communication, Control, and Computing (Allerton).

Active Learning from Multiple Knowledge Sources

Jennifer G. Dy, Glenn Fung, Rómer Rosales, 2012, AISTATS.

Predicting Readmission Risk with Institution Specific Prediction Models

Glenn Fung, Shipeng Yu, Balaji Krishnapuram, 2013, 2013 IEEE International Conference on Healthcare Informatics.

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

Glenn Fung, Luisa Polania, Dongning Wang, 2018, 2019 IEEE Winter Conference on Applications of Computer Vision (WACV).

Structure learning in random fields for heart motion abnormality detection

Mark W. Schmidt, Kevin P. Murphy, Glenn Fung, 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

Rule extraction from linear support vector machines

Glenn Fung, R. Bharat Rao, Sathyakama Sandilya, 2005, KDD '05.

Rule Extraction from Linear Support Vector Machines via Mathematical Programming

Glenn Fung, R. Bharat Rao, Sathyakama Sandilya, 2008, Rule Extraction from Support Vector Machines.

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

Hui Chen, Glenn Fung, R. Bharat Rao, 2008, AAAI.

Multiple-Instance Learning Algorithms for Computer-Aided Detection

Murat Dundar, Glenn Fung, R. Bharat Rao, 2008, IEEE Transactions on Biomedical Engineering.

Incremental Support Vector Machine Classification

Glenn Fung, Olvi L. Mangasarian, O. Mangasarian, 2002, SDM.

Convex Principal Feature Selection

Ying Cui, Jennifer G. Dy, Glenn Fung, 2010, SDM.

A Feature Selection Newton Method for Support Vector Machine Classification

Glenn Fung, Olvi L. Mangasarian, O. Mangasarian, 2004, Comput. Optim. Appl..

Mining Medical Images

Xiang Zhou, Murat Dundar, Jinbo Bi, 2009 .

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

Glenn Fung, R. Bharat Rao, Sriram Krishnan, 2007, Sixth International Conference on Machine Learning and Applications (ICMLA 2007).

Development, External Validation and Further Improvement of a Prediction Model for Survival of Non-small Cell Lung Cancer Patients Treated with (Chemo) Radiotherapy

Glenn Fung, Shipeng Yu, P. Lambin, 2008 .

A Comprehensive Overview of Basic Clustering Algorithms

Glenn Fung, Glenn Fung, 2001 .

Semi-supervised mixture of kernels via LPBoost methods

Murat Dundar, Jinbo Bi, Glenn Fung, 2005, Fifth IEEE International Conference on Data Mining (ICDM'05).

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

Murat Dundar, Glenn Fung, R. Bharat Rao, 2004, CARS.

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

Murat Dundar, Alok Gupta, Glenn Fung, 2004, CARS.

Sparse Fisher Discriminant Analysis for Computer Aided Detection

Murat Dundar, Jinbo Bi, Glenn Fung, 2005, SDM.

Equivalence of Minimal ℓ0- and ℓp-Norm Solutions of Linear Equalities, Inequalities and Linear Programs for Sufficiently Small p

Glenn Fung, Olvi L. Mangasarian, O. Mangasarian, 2011, J. Optim. Theory Appl..

The Limitations of Dosimetric Parameters for the Prediction of Radiation-Induced Lung Toxicity: An Approach Based on Machine Learning Techniques

R. B. Rao, Glenn Fung, D. Ruysscher, 2007 .

Kernel Fisher's Discriminant with Heterogeneous Kernels

Glenn Fung, Murat Dundar, 2009 .

Comparison of Bayesian network and support vector machine models for two-year survival prediction in lung cancer patients treated with radiotherapy.

D De Ruysscher, P Lambin, P. Lambin, 2010, Medical physics.

A fast iterative algorithm for fisher discriminant using heterogeneous kernels

Murat Dundar, Jinbo Bi, Glenn Fung, 2004, ICML.

Multiple-Instance Learning Algorithms for Computer-Aided Detection

R. B. Rao, Glenn Fung, M. Dundar, 2008, IEEE Transactions on Biomedical Engineering.

Batch Classification with Applications in Computer Aided Diagnosis

Jennifer G. Dy, Glenn Fung, R. Bharat Rao, 2006, ECML.

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

Glenn Fung, Jonathan Stoeckel, 2005, Fifth IEEE International Conference on Data Mining (ICDM'05).

Proximal Knowledge‐based Classification

Glenn Fung, Olvi L. Mangasarian, Edward W. Wild, 2009, Stat. Anal. Data Min..

Data selection for support vector machine classifiers

Glenn Fung, Olvi L. Mangasarian, O. Mangasarian, 2000, KDD '00.

Active Learning from Multiple Knowledge Sources

Jennifer G. Dy, R. B. Rao, Rómer Rosales, 2012, AISTATS.

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

Glenn Fung, Shipeng Yu, Balaji Krishnapuram, 2012, American Medical Informatics Association Annual Symposium.

Automated heart abnormality detection using sparse linear classifiers.

Jinbo Bi, Glenn Fung, Sriram Krishnan, 2007, IEEE engineering in medicine and biology magazine : the quarterly magazine of the Engineering in Medicine & Biology Society.