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Lawrence O. Hall

Publication record assembled from the DBLP archive of ranked conferences.

Papers indexed

82

Venues

20

Active years

1986–2024

Best venue rank

A*

Where they publish

Papers

82 indexed papers, newest first.

YearVenueTitleAuthors
2024CBMSActive Prompting of Vision Language Models for Human-in-the-loop Classification and Explanation of Microscopy Images.Abhiram Kandiyana, Peter R. Mouton, Lawrence O. Hall, Dmitry B. Goldgof
2024CBMSAnonymized Identity Tracking: Privacy Preserving Facial Encoding.Manas Sanjay Pakalapati, Dmitry B. Goldgof, Lawrence O. Hall, Ghada Zamzmi
2023CBMSUnsupervised Prostate Cancer Histopathology Image Segmentation via Meta-Learning.Nikolai Fetisov, Lawrence O. Hall, Dmitry B. Goldgof, Matthew B. Schabath
2023CBMSMIMO YOLO - A Multiple Input Multiple Output Model for Automatic Cell Counting.Hunter Morera, Palak Dave, Saeed S. Alahmari, Yaroslav Kolinko, Lawrence O. Hall, Dmitry B. Goldgof, Peter R. Mouton
2023SMCUsing SMOTE-based Data Augmentation for Social Media Time Series Prediction.Frederick Mubang, Lawrence O. Hall
2022ICMLASimulating New and Old Twitter User Activity with XGBoost and Probabilistic Hybrid Models.Frederick Mubang, Lawrence O. Hall
2020SMCSimulating Temporal User Activity on Social Networks with Sequence to Sequence Neural Models.Renhao Liu, Frederick Mubang, Lawrence O. Hall
2019SMCNeuroimaging Based Survival Time Prediction of GBM Patients Using CNNs from Small Data.Kaoutar Ben Ahmed, Lawrence O. Hall, Renhao Liu, Robert A. Gatenby, Dmitry B. Goldgof
2019SMCAutomatic Cell Counting using Active Deep Learning and Unbiased Stereology.Saeed S. Alahmari, Dmitry B. Goldgof, Lawrence O. Hall, Peter R. Mouton
2019SMCPredicting Longitudinal User Activity at Fine Time Granularity in Online Collaborative Platforms.Renhao Liu, Frederick Mubang, Lawrence O. Hall, Sameera Horawalavithana, Adriana Iamnitchi, John Skvoretz
2018ICMLAIterative Deep Learning Based Unbiased Stereology with Human-in-the-Loop.Saeed S. Alahmari, Dmitry B. Goldgof, Lawrence O. Hall, Palak Dave, Hady Ahmady Phoulady, Peter R. Mouton
2018IJCNNPredicting Nodule Malignancy using a CNN Ensemble Approach.Rahul Paul, Lawrence O. Hall, Dmitry B. Goldgof, Matthew B. Schabath, Robert J. Gillies
2018IJCNNRepresentation of Deep Features using Radiologist defined Semantic Features.Rahul Paul, Ying Liu, Qian Li, Lawrence O. Hall, Dmitry B. Goldgof, Yoganand Balagurunathan, Matthew B. Schabath, Robert J. Gillies
2017SMCSynthetic minority image over-sampling technique: How to improve AUC for glioblastoma patient survival prediction.Renhao Liu, Lawrence O. Hall, Kevin W. Bowyer, Dmitry B. Goldgof, Robert A. Gatenby, Kaoutar Ben Ahmed
2017SMCFinding label noise examples in large scale datasets.Ekambaram Rajmadhan, Dmitry B. Goldgof, Lawrence O. Hall
2016ICIPAutomatic quantification and classification of cervical cancer via Adaptive Nucleus Shape Modeling.Hady Ahmady Phoulady, Mu Zhou, Dmitry B. Goldgof, Lawrence O. Hall, Peter R. Mouton
2016ICPRSpectral sparsification in spectral clustering.Alireza Chakeri, Hamidreza Farhidzadeh, Lawrence O. Hall
2016IJCNNExploring deep features from brain tumor magnetic resonance images via transfer learning.Renhao Liu, Lawrence O. Hall, Dmitry B. Goldgof, Mu Zhou, Robert A. Gatenby, Kaoutar Ben Ahmed
2016SMCImproving malignancy prediction through feature selection informed by nodule size ranges in NLST.Dmitry Cherezov, Samuel H. Hawkins, Dmitry B. Goldgof, Lawrence O. Hall, Yoganand Balagurunathan, Robert J. Gillies, Matthew B. Schabath
2016SMCA quantitative histogram-based approach to predict treatment outcome for Soft Tissue Sarcomas using pre- and post-treatment MRIs.Hamidreza Farhidzadeh, Dmitry B. Goldgof, Lawrence O. Hall, Jacob G. Scott, Robert A. Gatenby, Robert J. Gillies, Meera Raghavan
2016SMCCombining deep neural network and traditional image features to improve survival prediction accuracy for lung cancer patients from diagnostic CT.Rahul Paul, Samuel H. Hawkins, Lawrence O. Hall, Dmitry B. Goldgof, Robert J. Gillies
2015ICDMLarge Data Clustering Using Quadratic Programming: A Comprehensive Quantitative Analysis.Alireza Chakeri, Lawrence O. Hall
2015SMCCorrelation Based Random Subspace Ensembles for Predicting Number of Axillary Lymph Node Metastases in Breast DCE-MRI Tumors.Baishali Chaudhury, Dmitry B. Goldgof, Lawrence O. Hall, Robert A. Gatenby, Robert J. Gillies, Jennifer S. Drukteinis
2015SMCTexture Feature Analysis to Predict Metastatic and Necrotic Soft Tissue Sarcomas.Hamidreza Farhidzadeh, Dmitry B. Goldgof, Lawrence O. Hall, Robert A. Gatenby, Robert J. Gillies, Meera Raghavan
2015SMCA Robust Approach for Automated Lung Segmentation in Thoracic CT.Hailing Zhou, Dmitry B. Goldgof, Samuel H. Hawkins, Lei Wei, Ying Liu, Douglas C. Creighton, Robert J. Gillies, Lawrence O. Hall, Saeid Nahavandi
2014CIDMRelational data partitioning using evolutionary game theory.Lawrence O. Hall, Alireza Chakeri
2014ICPRDominant Sets as a Framework for Cluster Ensembles: An Evolutionary Game Theory Approach.Alireza Chakeri, Lawrence O. Hall
2014ICPRExploring Brain Tumor Heterogeneity for Survival Time Prediction.Mu Zhou, Lawrence O. Hall, Dmitry B. Goldgof
2014SMCUsing features from tumor subregions of breast DCE-MRI for estrogen receptor status prediction.Baishali Chaudhury, Mu Zhou, Dmitry B. Goldgof, Lawrence O. Hall, Robert A. Gatenby, Robert J. Gillies, Jennifer S. Drukteinis
2014SMCExperiments with large ensembles for segmentation and classification of cervical cancer biopsy images.Hady Ahmady Phoulady, Baishali Chaudhury, Dmitry B. Goldgof, Lawrence O. Hall, Peter R. Mouton, Ardeshir Hakam, Erin M. Siegel
2013ICIAPAn Ensemble Algorithm Framework for Automated Stereology of Cervical Cancer.Baishali Chaudhury, Hady Ahmady Phoulady, Dmitry B. Goldgof, Lawrence O. Hall, Peter R. Mouton, Ardeshir Hakam, Erin M. Siegel
2013SMCEffect of Texture Features in Computer Aided Diagnosis of Pulmonary Nodules in Low-Dose Computed Tomography.Henry Krewer, Benjamin Geiger, Lawrence O. Hall, Dmitry B. Goldgof, Yuhua Gu, Melvyn Tockman, Robert J. Gillies
2013SMCA Texture Feature Ranking Model for Predicting Survival Time of Brain Tumor Patients.Mu Zhou, Lawrence O. Hall, Dmitry B. Goldgof, Robert A. Gatenby, Robert J. Gillies
2012CBMSA novel algorithm for automated counting of stained cells on thick tissue sections.Baishali Chaudhury, Kurt Kramer, Daniel Elozory, Gerry Hernandez, Dmitry B. Goldgof, Lawrence O. Hall, Peter R. Mouton
2012ICPRLabel-noise reduction with support vector machines.Sergiy Fefilatyev, Matthew Shreve, Kurt Kramer, Lawrence O. Hall, Dmitry B. Goldgof, Rangachar Kasturi, Kendra Daly, Andrew Remsen, Horst Bunke
2011CIDMIncreased classification accuracy and speedup through pair-wise feature selection for support vector machines.Kurt Kramer, Dmitry B. Goldgof, Lawrence O. Hall, Andrew Remsen
2011ICDMDetection of Anomalous Particles from the Deepwater Horizon Oil Spill Using the SIPPER3 Underwater Imaging Platform.Sergiy Fefilatyev, Kurt Kramer, Lawrence O. Hall, Dmitry B. Goldgof, Rangachar Kasturi, Andrew Remsen, Kendra Daly
2011SMCDeveloping a classifier model for lung tumors in CT-scan images.Satrajit Basu, Lawrence O. Hall, Dmitry B. Goldgof, Yuhua Gu, Virendra Kumar, Jung Choi, Robert J. Gillies, Robert A. Gatenby
2011SMCProcedure for stability analysis of gene selection from cross-site gene expression data.John N. Korecki, Lawrence O. Hall, Dmitry B. Goldgof, Steven Eschrich
2010SMCFiltering for improved gene selection on microarray data.Juana Canul-Reich, Lawrence O. Hall, Dmitry B. Goldgof, Steven Eschrich
2010SMCEvaluating scalable fuzzy clustering.Yuhua Gu, Lawrence O. Hall, Dmitry B. Goldgof
2009SMCAutomatic Red Tide Detection from MODIS Satellite Images.Weijian Cheng, Lawrence O. Hall, Dmitry B. Goldgof, Chuanmin Hu, Inia M. Soto
2008SMCFeature selection for microarray data by AUC analysis.Juana Canul-Reich, Lawrence O. Hall, Dmitry B. Goldgof, Steven Eschrich
2007BIBEMultivariate Feature Selection using Random Subspace Classifiers for Gene Expression Data.Vidya P. Kamath, Lawrence O. Hall, Timothy Yeatman, Steven Eschrich
2007SMCClinical deployment of a medical expert system to increase accruals for clinical trials: Challenges.Sergiy Fefilatyev, Tim V. Ivanovskiy, Lawrence O. Hall, Dmitry B. Goldgof, Shibendra S. Pobi, Halina Greenstien, Amit P. Pathak, Christopher R. Garret
2007SMCA fuzzy c means variant for clustering evolving data streams.Prodip Hore, Lawrence O. Hall, Dmitry B. Goldgof
2006ICMLAHorizon Detection Using Machine Learning Techniques.Sergiy Fefilatyev, Volha Smarodzinava, Lawrence O. Hall, Dmitry B. Goldgof
2006ICPRMining for Implications in Medical Data.Cindy L. Bethel, Lawrence O. Hall, Dmitry B. Goldgof
2006IJCNNPredicting Juvenile Diabetes from Clinical Test Results.Shibendra S. Pobi, Lawrence O. Hall
2006ICTAILearning to Predict Salient Regions from Disjoint and Skewed Training Sets.Larry Shoemaker, Robert E. Banfield, Lawrence O. Hall, Kevin W. Bowyer, W. Philip Kegelmeyer
2006SMCA Cluster Ensemble Framework for Large Data sets.Prodip Hore, Lawrence O. Hall, Dmitry B. Goldgof
2005ICDMBit Reduction Support Vector Machine.Tong Luo, Lawrence O. Hall, Dmitry B. Goldgof, Andrew Remsen
2005SMCSequence tolerant segmentation system of brain MRI.Yuhua Gu, Lawrence O. Hall, Dmitry B. Goldgof, Parag M. Kanade, F. Reed Murtagh
2004CBMSUsing Probabilistic Methods to Optimize Data Entry in Accrual of Patients to Clinical Trials.Bhavesh D. Goswami, Lawrence O. Hall, Dmitry B. Goldgof, Eugene Fink, Jeffrey P. Krischer
2004ICPRActive Learning to Recognize Multiple Types of Plankton.Tong Luo, Kurt Kramer, Dmitry B. Goldgof, Lawrence O. Hall, Scott Samson, Andrew Remsen, Thomas Hopkins
2004SMCLearning a model from spatially disjoint data.Lawrence O. Hall, Divya Bhadoria, Kevin W. Bowyer
2004SMCDecision trees work better than feed-forward back-prop neural nets for a specific class of problems.Xiaomei Liu, Kevin W. Bowyer, Lawrence O. Hall
2003ICDMComparing Pure Parallel Ensemble Creation Techniques Against Bagging.Lawrence O. Hall, Kevin W. Bowyer, Robert E. Banfield, Divya Bhadoria, W. Philip Kegelmeyer, Steven Eschrich
2003SMCExperiments on the automated selection of patients for clinical trials.Eugene Fink, Lawrence O. Hall, Dmitry B. Goldgof, Bhavesh D. Goswami, Matthew Boonstra, Jeffrey P. Krischer
2003SMCWhy are neural networks sometimes much more accurate than decision trees: an analysis on a bio-informatics problem.Lawrence O. Hall, Xiaomei Liu, Kevin W. Bowyer, Robert E. Banfield
2003SMCLearning to recognize plankton.Tong Luo, Kurt Kramer, Dmitry B. Goldgof, Lawrence O. Hall, Scott Samson, Andrew Remsen, Thomas Hopkins
2002CECA constrained genetic approach for reconstructing Young's modulus of elastic objects from boundary displacement measurements.Yong Zhang, Lawrence O. Hall, Dmitry B. Goldgof, Sudeep Sarkar
2002ICTAIError-Based Pruning of Decision Trees Grown on Very Large Data Sets Can Work!Lawrence O. Hall, Richard Collins, Kevin W. Bowyer, Robert E. Banfield
2002KDDGeneralization Methods in Bioinformatics.Steven Eschrich, Nitesh V. Chawla, Lawrence O. Hall
2001CVPRBagging Is a Small-Data-Set Phenomenon.Nitesh V. Chawla, Thomas E. Moore, Kevin W. Bowyer, Lawrence O. Hall, Clayton Springer, W. Philip Kegelmeyer
2001ICDARText Extraction from Color Documents - Clustering Approaches in Three and Four Dimensions.T. Perroud, Karin Sobottka, Horst Bunke, Lawrence O. Hall
2001ICDMCreating Ensembles of Classifiers.Nitesh V. Chawla, Steven Eschrich, Lawrence O. Hall
2001KDDInvestigation of bagging-like effects and decision trees versus neural nets in protein secondary structure prediction.Nitesh V. Chawla, Thomas E. Moore, Kevin W. Bowyer, Lawrence O. Hall, Clayton Springer, W. Philip Kegelmeyer
2001SMCData mining from extreme data sets: very large and/or very skewed data sets.Lawrence O. Hall
2000ICPRFinding Green River in SeaWiFS Satellite Images.Wensheng Yao, Lawrence O. Hall, Dmitry B. Goldgof, Frank E. Mller-Karger
2000SMCA parallel decision tree builder for mining very large visualization datasets.Kevin W. Bowyer, Lawrence O. Hall, Thomas Moore, Nitesh V. Chawla, W. Philip Kegelmeyer
1999KDDLearning Rules from Distributed Data.Lawrence O. Hall, Nitesh V. Chawla, Kevin W. Bowyer, W. Philip Kegelmeyer
1998FlAIRSA Qualitative Expert System for Clinical Trial Assignment.Sanjukta Bhanja, Lynn M. Fletcher-Heath, Lawrence O. Hall, Dmitry B. Goldgof, Jeffrey P. Krischer
1998SMCDecision tree learning on very large data sets.Lawrence O. Hall, Nitesh V. Chawla, Kevin W. Bowyer
1996ICPRKnowledge-based classification of CZCS images and monitoring of red tides off the west Florida shelf.Mingrui Zhang, Lawrence O. Hall, Dmitry B. Goldgof
1995IJCAIUsing Fuzzy Information in Knowledge Guided Segmentation of Brain Tumors.Matthew C. Clark, Lawrence O. Hall, Dmitry B. Goldgof, Martin L. Silbiger
1994ICECGenetic Algorithm Guided Clustering.James C. Bezdek, Srinivas Boggavarapu, Lawrence O. Hall, Amine Bensaid
1994ICPRKnowledge based (re-)clustering.Matthew C. Clark, Lawrence O. Hall, Chunlin Li, Dmitry B. Goldgof
1993IJCAILearning Fuzzy Membership Functions in a Function-Based Object Recognition System.Kevin S. Woods, Diane J. Cook, Lawrence O. Hall, Louise Stark, Kevin W. Bowyer
1992ICTAIA Hybrid/Symbolic Connectionist Production System.Katsuaki Sanou, Steve G. Romaniuk, Lawrence O. Hall
1990AAAIA Hybrid Connectionist, Symbolic Learning System.Lawrence O. Hall, Steve G. Romaniuk
1986IASNew Concepts for Expert Systems Capable of Intelligence in an Imprecise Environment.Lawrence O. Hall, Wyllis Bandler, Abraham Kandel