Lawrence O. Hall

ORCID

Publication Activity (10 Years)

Years Active: 1985-2024
Publications (10 Years): 55

Top Venues

SMC

Medical Imaging: Computer-Aided Diagnosis

CoRR

IEEE Access

Publications

Shashwat Kumar, Francis Hahn, Xinming Ou, Dmitry B. Goldgof, Lawrence O. Hall, Jay Ligatti, S. Raj Rajagopalan, Armin Ziaie Tabari
A Preliminary Study on Using Large Language Models in Software Pentesting. CoRR (2024)
Manas Sanjay Pakalapati, Dmitry B. Goldgof, Lawrence O. Hall, Ghada Zamzmi
Anonymized Identity Tracking: Privacy Preserving Facial Encoding. CBMS (2024)
Saeed S. Alahmari, Dmitry B. Goldgof, Lawrence O. Hall, Peter R. Mouton
A Review of Nuclei Detection and Segmentation on Microscopy Images Using Deep Learning With Applications to Unbiased Stereology Counting. IEEE Trans. Neural Networks Learn. Syst. 35 (6) (2024)
Abhiram Kandiyana, Peter R. Mouton, Lawrence O. Hall, Dmitry B. Goldgof
Active Prompting of Vision Language Models for Human-in-the-loop Classification and Explanation of Microscopy Images. CBMS (2024)
Adriana Iamnitchi, Lawrence O. Hall, Sameera Horawalavithana, Frederick Mubang, Kin Wai Ng, John Skvoretz
Modeling information diffusion in social media: data-driven observations. Frontiers Big Data 6 (2024)
Hunter Morera, Palak Dave, Saeed S. Alahmari, Yaroslav Kolinko, Lawrence O. Hall, Dmitry B. Goldgof, Peter R. Mouton
MIMO YOLO - A Multiple Input Multiple Output Model for Automatic Cell Counting. CBMS (2023)
Nikolai Fetisov, Lawrence O. Hall, Dmitry B. Goldgof, Matthew B. Schabath
Unsupervised Prostate Cancer Histopathology Image Segmentation via Meta-Learning. CBMS (2023)
Kin Wai Ng, Frederick Mubang, Lawrence O. Hall, John Skvoretz, Adriana Iamnitchi
Experimental evaluation of baselines for forecasting social media timeseries. EPJ Data Sci. 12 (1) (2023)
Frederick Mubang, Lawrence O. Hall
Using SMOTE-based Data Augmentation for Social Media Time Series Prediction. SMC (2023)
Frederick Mubang, Lawrence O. Hall
VAM: An End-to-End Simulator for Time Series Regression and Temporal Link Prediction in Social Media Networks. IEEE Trans. Comput. Soc. Syst. 10 (4) (2023)
Hunter Morera, Palak Dave, Yaroslav Kolinko, Kurtis Allen, Saeed S. Alahmari, Dmitry B. Goldgof, Lawrence O. Hall, Peter R. Mouton
Classification of global microglia proliferation based on deep learning with local images. Medical Imaging: Image Processing (2022)
Frederick Mubang, Lawrence O. Hall
Simulating User-Level Twitter Activity with XGBoost and Probabilistic Hybrid Models. CoRR (2022)
Kin Wai Ng, Frederick Mubang, Lawrence O. Hall, John Skvoretz, Adriana Iamnitchi
Experimental Evaluation of Baselines for Forecasting Social Media Timeseries. CoRR (2022)
Hunter Morera, Roshan Warman, Azubuogu Anudu, Chukwudumebi Uche, Ivana Radosavljevic, Nikhil Reddy, Ahan Kayastha, Niharika Baviriseaty, Rahul Mhaskar, Andrew A. Borkowski, Patrick Brady, Satish Singh, Gerard Mullin, José Lezama, Lawrence O. Hall, Dmitry B. Goldgof, Gitanjali Vidyarthi
Reduction of Video Capsule Endoscopy Reading Times Using Deep Learning with Small Data. Algorithms 15 (10) (2022)
Frederick Mubang, Lawrence O. Hall
Simulating New and Old Twitter User Activity with XGBoost and Probabilistic Hybrid Models. ICMLA (2022)
Kaoutar Ben Ahmed, Lawrence O. Hall, Dmitry B. Goldgof, Ryan Fogarty
Achieving Multisite Generalization for CNN-Based Disease Diagnosis Models by Mitigating Shortcut Learning. IEEE Access 10 (2022)
Kaoutar Ben Ahmed, Gregory M. Goldgof, Rahul Paul, Dmitry B. Goldgof, Lawrence O. Hall
Discovery of a Generalization Gap of Convolutional Neural Networks on COVID-19 X-Rays Classification. IEEE Access 9 (2021)
Rahul Paul, Sherzod Kariev, Dmitry Cherezov, Matthew B. Schabath, Robert J. Gillies, Lawrence O. Hall, Dmitry B. Goldgof
Deep radiomics: deep learning on radiomics texture images. Medical Imaging: Computer-Aided Diagnosis (2021)
Kaoutar Ben Ahmed, Lawrence O. Hall, Dmitry B. Goldgof, Gregory M. Goldgof, Rahul Paul
Deep Learning Models May Spuriously Classify Covid-19 from X-ray Images Based on Confounders. CoRR (2021)
Subhashis Banerjee, Sushmita Mitra, Lawrence O. Hall
Analysis of MRI Biomarkers for Brain Cancer Survival Prediction. CoRR (2021)
Saeed S. Alahmari, Dmitry B. Goldgof, Peter R. Mouton, Lawrence O. Hall
Challenges for the Repeatability of Deep Learning Models. IEEE Access 8 (2020)
Rahul Paul, Matthew B. Schabath, Robert J. Gillies, Lawrence O. Hall, Dmitry B. Goldgof
Mitigating Adversarial Attacks on Medical Image Understanding Systems. ISBI (2020)
Renhao Liu, Frederick Mubang, Lawrence O. Hall
Simulating Temporal User Activity on Social Networks with Sequence to Sequence Neural Models. SMC (2020)
Lawrence O. Hall, Rahul Paul, Dmitry B. Goldgof, Gregory M. Goldgof
Finding Covid-19 from Chest X-rays using Deep Learning on a Small Dataset. CoRR (2020)
Rahul Paul, Matthew B. Schabath, Robert J. Gillies, Lawrence O. Hall, Dmitry B. Goldgof
Convolutional Neural Network ensembles for accurate lung nodule malignancy prediction 2 years in the future. Comput. Biol. Medicine 122 (2020)
Valerie Cross, Michael Zmuda, Rahul Paul, Lawrence O. Hall
Fuzzy Set Similarity for Feature Selection in Classification. FUZZ-IEEE (2020)
Renhao Liu, Frederick Mubang, Lawrence O. Hall, Sameera Horawalavithana, Adriana Iamnitchi, John Skvoretz
Predicting Longitudinal User Activity at Fine Time Granularity in Online Collaborative Platforms. SMC (2019)
Saeed S. Alahmari, Dmitry B. Goldgof, Lawrence O. Hall, Peter R. Mouton
Automatic Cell Counting using Active Deep Learning and Unbiased Stereology. SMC (2019)
Saeed S. Alahmari, Dmitry B. Goldgof, Lawrence O. Hall, Palak Dave, Hady Ahmady Phoulady, Peter R. Mouton
Iterative Deep Learning Based Unbiased Stereology With Human-in-the-Loop. CoRR (2019)
Sameera Horawalavithana, Abhishek Bhattacharjee, Renhao Liu, Nazim Choudhury, Lawrence O. Hall, Adriana Iamnitchi
Mentions of Security Vulnerabilities on Reddit, Twitter and GitHub. WI (2019)
Rahul Paul, Dmitry Cherezov, Matthew B. Schabath, Robert J. Gillies, Lawrence O. Hall, Dmitry B. Goldgof
Towards deep radiomics: nodule malignancy prediction using CNNs on feature images. Medical Imaging: Computer-Aided Diagnosis (2019)
Kaoutar Ben Ahmed, Lawrence O. Hall, Renhao Liu, Robert A. Gatenby, Dmitry B. Goldgof
Neuroimaging Based Survival Time Prediction of GBM Patients Using CNNs from Small Data. SMC (2019)
Rahul Paul, Lawrence O. Hall, Dmitry B. Goldgof, Matthew B. Schabath, Robert J. Gillies
Predicting Nodule Malignancy using a CNN Ensemble Approach. IJCNN (2018)
Saeed S. Alahmari, Dmitry Cherezov, Dmitry B. Goldgof, Lawrence O. Hall, Robert J. Gillies, Matthew B. Schabath
Delta Radiomics Improves Pulmonary Nodule Malignancy Prediction in Lung Cancer Screening. IEEE Access 6 (2018)
Rahul Paul, Ying Liu, Qian Li, Lawrence O. Hall, Dmitry B. Goldgof, Yoganand Balagurunathan, Matthew B. Schabath, Robert J. Gillies
Representation of Deep Features using Radiologist defined Semantic Features. IJCNN (2018)
Saeed S. Alahmari, Dmitry B. Goldgof, Lawrence O. Hall, Palak Dave, Hady Ahmady Phoulady, Peter R. Mouton
Iterative Deep Learning Based Unbiased Stereology with Human-in-the-Loop. ICMLA (2018)
Rahul Paul, Muhammad Shafiq-ul-Hassan, Eduardo G. Moros, Robert J. Gillies, Lawrence O. Hall, Dmitry B. Goldgof
Stability of deep features across CT scanners and field of view using a physical phantom. Medical Imaging: Computer-Aided Diagnosis (2018)
Hady Ahmady Phoulady, Dmitry B. Goldgof, Lawrence O. Hall, Peter R. Mouton
A framework for nucleus and overlapping cytoplasm segmentation in cervical cytology extended depth of field and volume images. Comput. Medical Imaging Graph. 59 (2017)
Kaoutar Ben Ahmed, Lawrence O. Hall, Dmitry B. Goldgof, Renhao Liu, Robert A. Gatenby
Fine-tuning convolutional deep features for MRI based brain tumor classification. Medical Imaging: Computer-Aided Diagnosis (2017)
Meng Fang, Jie Yin, Lawrence O. Hall, Dacheng Tao
Active Multitask Learning With Trace Norm Regularization Based on Excess Risk. IEEE Trans. Cybern. 47 (11) (2017)
Renhao Liu, Lawrence O. Hall, Kevin W. Bowyer, Dmitry B. Goldgof, Robert A. Gatenby, Kaoutar Ben Ahmed
Synthetic minority image over-sampling technique: How to improve AUC for glioblastoma patient survival prediction. SMC (2017)
Ekambaram Rajmadhan, Dmitry B. Goldgof, Lawrence O. Hall
Finding label noise examples in large scale datasets. SMC (2017)
Renhao Liu, Lawrence O. Hall, Dmitry B. Goldgof, Mu Zhou, Robert A. Gatenby, Kaoutar Ben Ahmed
Exploring deep features from brain tumor magnetic resonance images via transfer learning. IJCNN (2016)
Benjamin Geiger, Samuel H. Hawkins, Lawrence O. Hall, Dmitry B. Goldgof, Yoganand Balagurunathan, Robert A. Gatenby, Robert J. Gillies
Change descriptors for determining nodule malignancy in national lung screening trial CT screening images. Medical Imaging: Computer-Aided Diagnosis (2016)
Hamidreza Farhidzadeh, Joo Y. Kim, Jacob G. Scott, Dmitry B. Goldgof, Lawrence O. Hall, Louis B. Harrison
Classification of progression free survival with nasopharyngeal carcinoma tumors. Medical Imaging: Computer-Aided Diagnosis (2016)
Baishali Chaudhury, Mu Zhou, Hamidreza Farhidzadeh, Dmitry B. Goldgof, Lawrence O. Hall, Robert A. Gatenby, Robert J. Gillies, Robert J. Weinfurtner, Jennifer S. Drukteinis
Predicting Ki67% expression from DCE-MR images of breast tumors using textural kinetic features in tumor habitats. Medical Imaging: Computer-Aided Diagnosis (2016)
Hamidreza Farhidzadeh, Baishali Chaudhury, Jacob G. Scott, Dmitry B. Goldgof, Lawrence O. Hall, Robert A. Gatenby, Robert J. Gillies, Meera Raghavan
Signal intensity analysis of ecological defined habitat in soft tissue sarcomas to predict metastasis development. Medical Imaging: Computer-Aided Diagnosis (2016)
Dmitry Cherezov, Samuel H. Hawkins, Dmitry B. Goldgof, Lawrence O. Hall, Yoganand Balagurunathan, Robert J. Gillies, Matthew B. Schabath
Improving malignancy prediction through feature selection informed by nodule size ranges in NLST. SMC (2016)
Ekambaram Rajmadhan, Sergiy Fefilatyev, Matthew Shreve, Kurt Kramer, Lawrence O. Hall, Dmitry B. Goldgof, Rangachar Kasturi
Active cleaning of label noise. Pattern Recognit. 51 (2016)
Rahul Paul, Samuel H. Hawkins, Lawrence O. Hall, Dmitry B. Goldgof, Robert J. Gillies
Combining deep neural network and traditional image features to improve survival prediction accuracy for lung cancer patients from diagnostic CT. SMC (2016)
Hady Ahmady Phoulady, Dmitry B. Goldgof, Lawrence O. Hall, Peter R. Mouton
A new approach to detect and segment overlapping cells in multi-layer cervical cell volume images. ISBI (2016)
Hady Ahmady Phoulady, Dmitry B. Goldgof, Lawrence O. Hall, Peter R. Mouton
Nucleus segmentation in histology images with hierarchical multilevel thresholding. Medical Imaging: Digital Pathology (2016)
Hady Ahmady Phoulady, Mu Zhou, Dmitry B. Goldgof, Lawrence O. Hall, Peter R. Mouton
Automatic quantification and classification of cervical cancer via Adaptive Nucleus Shape Modeling. ICIP (2016)
Hamidreza Farhidzadeh, Dmitry B. Goldgof, Lawrence O. Hall, Jacob G. Scott, Robert A. Gatenby, Robert J. Gillies, Meera Raghavan
A quantitative histogram-based approach to predict treatment outcome for Soft Tissue Sarcomas using pre- and post-treatment MRIs. SMC (2016)
Alireza Chakeri, Hamidreza Farhidzadeh, Lawrence O. Hall
Spectral sparsification in spectral clustering. ICPR (2016)
Hamidreza Farhidzadeh, Dmitry B. Goldgof, Lawrence O. Hall, Robert A. Gatenby, Robert J. Gillies, Meera Raghavan
Texture Feature Analysis to Predict Metastatic and Necrotic Soft Tissue Sarcomas. SMC (2015)
Mu Zhou, Lawrence O. Hall, Dmitry B. Goldgof, Robert J. Gillies, Robert A. Gatenby
Imbalanced learning for clinical survival group prediction of brain tumor patients. Medical Imaging: Computer-Aided Diagnosis (2015)
Hailing Zhou, Dmitry B. Goldgof, Samuel H. Hawkins, Lei Wei, Ying Liu, Douglas C. Creighton, Robert J. Gillies, Lawrence O. Hall, Saeid Nahavandi
A Robust Approach for Automated Lung Segmentation in Thoracic CT. SMC (2015)
Hamidreza Farhidzadeh, Baishali Chaudhury, Mu Zhou, Dmitry B. Goldgof, Lawrence O. Hall, Robert A. Gatenby, Robert J. Gillies, Meera Raghavan
Prediction of treatment outcome in soft tissue sarcoma based on radiologically defined habitats. Medical Imaging: Computer-Aided Diagnosis (2015)
Baishali Chaudhury, Dmitry B. Goldgof, Lawrence O. Hall, Robert A. Gatenby, Robert J. Gillies, Jennifer S. Drukteinis
Correlation Based Random Subspace Ensembles for Predicting Number of Axillary Lymph Node Metastases in Breast DCE-MRI Tumors. SMC (2015)
Alireza Chakeri, Lawrence O. Hall
Large Data Clustering Using Quadratic Programming: A Comprehensive Quantitative Analysis. ICDM Workshops (2015)
Baishali Chaudhury, Mu Zhou, Dmitry B. Goldgof, Lawrence O. Hall, Robert A. Gatenby, Robert J. Gillies, Jennifer S. Drukteinis
Identifying metastatic breast tumors using textural kinetic features of a contrast based habitat in DCE-MRI. Medical Imaging: Computer-Aided Diagnosis (2015)
Mu Zhou, Lawrence O. Hall, Dmitry B. Goldgof, Robin Russo, Robert J. Gillies, Robert A. Gatenby
Decoding brain cancer dynamics: a quantitative histogram-based approach using temporal MRI. Medical Imaging: Computer-Aided Diagnosis (2015)
Hamidreza Farhidzadeh, Mu Zhou, Dmitry B. Goldgof, Lawrence O. Hall, Meera Raghavan, Robert A. Gatenby
Prediction of treatment response and metastatic disease in soft tissue sarcoma. Medical Imaging: Computer-Aided Diagnosis (2014)
Hady Ahmady Phoulady, Baishali Chaudhury, Dmitry B. Goldgof, Lawrence O. Hall, Peter R. Mouton, Ardeshir Hakam, Erin M. Siegel
Experiments with large ensembles for segmentation and classification of cervical cancer biopsy images. SMC (2014)
Baishali Chaudhury, Mu Zhou, Dmitry B. Goldgof, Lawrence O. Hall, Robert A. Gatenby, Robert J. Gillies, Jennifer S. Drukteinis
Using features from tumor subregions of breast DCE-MRI for estrogen receptor status prediction. SMC (2014)
Mu Zhou, Lawrence O. Hall, Dmitry B. Goldgof
Exploring Brain Tumor Heterogeneity for Survival Time Prediction. ICPR (2014)
Lawrence O. Hall, Alireza Chakeri
Relational data partitioning using evolutionary game theory. CIDM (2014)
Yoganand Balagurunathan, Virendra Kumar, Yuhua Gu, Jongphil Kim, Hua Wang, Ying Liu, Dmitry B. Goldgof, Lawrence O. Hall, René Korn, Binsheng Zhao, Lawrence H. Schwartz, Satrajit Basu, Steven Eschrich, Robert A. Gatenby, Robert J. Gillies
Test-Retest Reproducibility Analysis of Lung CT Image Features. J. Digit. Imaging 27 (6) (2014)
Baishali Chaudhury, Lawrence O. Hall, Dmitry B. Goldgof, Robert A. Gatenby, Robert J. Gillies, Jennifer S. Drukteinis
New method for predicting estrogen receptor status utilizing breast MRI texture kinetic analysis. Medical Imaging: Computer-Aided Diagnosis (2014)
Jonathon K. Parker, Lawrence O. Hall
Accelerating Fuzzy-C Means Using an Estimated Subsample Size. IEEE Trans. Fuzzy Syst. 22 (5) (2014)
Samuel H. Hawkins, John N. Korecki, Yoganand Balagurunathan, Yuhua Gu, Virendra Kumar, Satrajit Basu, Lawrence O. Hall, Dmitry B. Goldgof, Robert A. Gatenby, Robert J. Gillies
Predicting Outcomes of Nonsmall Cell Lung Cancer Using CT Image Features. IEEE Access 2 (2014)
Alireza Chakeri, Lawrence O. Hall
Dominant Sets as a Framework for Cluster Ensembles: An Evolutionary Game Theory Approach. ICPR (2014)
Henry Krewer, Benjamin Geiger, Lawrence O. Hall, Dmitry B. Goldgof, Yuhua Gu, Melvyn Tockman, Robert J. Gillies
Effect of Texture Features in Computer Aided Diagnosis of Pulmonary Nodules in Low-Dose Computed Tomography. SMC (2013)
Alireza Chakeri, Iman Nekooeimehr, Lawrence O. Hall
Dempster-Shafer theory of evidence in Single Pass Fuzzy C Means. FUZZ-IEEE (2013)
Baishali Chaudhury, Hady Ahmady Phoulady, Dmitry B. Goldgof, Lawrence O. Hall, Peter R. Mouton, Ardeshir Hakam, Erin M. Siegel
An Ensemble Algorithm Framework for Automated Stereology of Cervical Cancer. ICIAP (1) (2013)
Mu Zhou, Lawrence O. Hall, Dmitry B. Goldgof, Robert A. Gatenby, Robert J. Gillies
A Texture Feature Ranking Model for Predicting Survival Time of Brain Tumor Patients. SMC (2013)
Mu Zhou, Lawrence O. Hall, Dmitry B. Goldgof, Robert J. Gillies, Robert A. Gatenby
Survival time prediction of patients with glioblastoma multiforme tumors using spatial distance measurement. Medical Imaging: Computer-Aided Diagnosis (2013)
Yuhua Gu, Virendra Kumar, Lawrence O. Hall, Dmitry B. Goldgof, Ching-Yen Li, René Korn, Claus Bendtsen, Emmanuel Rios Velazquez, Andre Dekker, Hugo J. W. L. Aerts, Philippe Lambin, Xiuli Li, Jie Tian, Robert A. Gatenby, Robert J. Gillies
Automated delineation of lung tumors from CT images using a single click ensemble segmentation approach. Pattern Recognit. 46 (3) (2013)
Lawrence O. Hall
Objective function-based clustering. WIREs Data Mining Knowl. Discov. 2 (4) (2012)
Sergiy Fefilatyev, Matthew Shreve, Kurt Kramer, Lawrence O. Hall, Dmitry B. Goldgof, Rangachar Kasturi, Kendra Daly, Andrew Remsen, Horst Bunke
Label-noise reduction with support vector machines. ICPR (2012)
Lawrence O. Hall
Exploring Big Data with Scalable Soft Clustering. SMPS (2012)
Juana Canul-Reich, Lawrence O. Hall, Dmitry B. Goldgof, John N. Korecki, Steven Eschrich
Iterative Feature perturbation as a gene Selector for microarray Data. Int. J. Pattern Recognit. Artif. Intell. 26 (5) (2012)
Timothy C. Havens, James C. Bezdek, Christopher Leckie, Lawrence O. Hall, Marimuthu Palaniswami
Fuzzy c-Means Algorithms for Very Large Data. IEEE Trans. Fuzzy Syst. 20 (6) (2012)
Baishali Chaudhury, Kurt Kramer, Daniel Elozory, Gerry Hernandez, Dmitry B. Goldgof, Lawrence O. Hall, Peter R. Mouton
A novel algorithm for automated counting of stained cells on thick tissue sections. CBMS (2012)
Jonathon K. Parker, Lawrence O. Hall, James C. Bezdek
Comparison of scalable fuzzy clustering methods. FUZZ-IEEE (2012)
Satrajit Basu, Lawrence O. Hall, Dmitry B. Goldgof, Yuhua Gu, Virendra Kumar, Jung Choi, Robert J. Gillies, Robert A. Gatenby
Developing a classifier model for lung tumors in CT-scan images. SMC (2011)
Larry Shoemaker, Robert E. Banfield, Lawrence O. Hall, Kevin W. Bowyer, W. Philip Kegelmeyer
Detecting and ordering salient regions. Data Min. Knowl. Discov. 22 (1-2) (2011)
Kevin W. Bowyer, Nitesh V. Chawla, Lawrence O. Hall, W. Philip Kegelmeyer
SMOTE: Synthetic Minority Over-sampling Technique CoRR (2011)
John N. Korecki, Lawrence O. Hall, Dmitry B. Goldgof, Steven Eschrich
Procedure for stability analysis of gene selection from cross-site gene expression data. SMC (2011)
Sergiy Fefilatyev, Kurt Kramer, Lawrence O. Hall, Dmitry B. Goldgof, Rangachar Kasturi, Andrew Remsen, Kendra Daly
Detection of Anomalous Particles from the Deepwater Horizon Oil Spill Using the SIPPER3 Underwater Imaging Platform. ICDM Workshops (2011)
Kurt Kramer, Dmitry B. Goldgof, Lawrence O. Hall, Andrew Remsen
Increased classification accuracy and speedup through pair-wise feature selection for support vector machines. CIDM (2011)
Daniel T. Elozory, Om Pavithra Bonam, Kurt Kramer, Dmitry B. Goldgof, Lawrence O. Hall, Osvaldo Mangual, Peter R. Mouton
Automatic location of microscopic focal planes for computerized stereology. Medical Imaging: Computer-Aided Diagnosis (2011)
Om Pavithra Bonam, Daniel Elozory, Kurt Kramer, Dmitry B. Goldgof, Lawrence O. Hall, Osvaldo Mangual, Peter R. Mouton
Toward automated quantification of biological microstructures using unbiased stereology. Medical Imaging: Computer-Aided Diagnosis (2011)
Larry Shoemaker, Lawrence O. Hall
Anomaly Detection Using Ensembles. MCS (2011)
Lawrence O. Hall, Dmitry B. Goldgof
Convergence of the Single-Pass and Online Fuzzy C-Means Algorithms. IEEE Trans. Fuzzy Syst. 19 (4) (2011)
Lawrence O. Hall, Dmitry B. Goldgof
On convergence properties of the singlepass and online fuzzy c-means algorithm. FUZZ-IEEE (2010)
Yuhua Gu, Lawrence O. Hall, Dmitry B. Goldgof
Evaluating scalable fuzzy clustering. SMC (2010)
Jonathon K. Parker, Lawrence O. Hall, Abraham Kandel
Scalable fuzzy neighborhood DBSCAN. FUZZ-IEEE (2010)
Juana Canul-Reich, Lawrence O. Hall, Dmitry B. Goldgof, Steven Eschrich
Filtering for improved gene selection on microarray data. SMC (2010)

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Publication Activity (10 Years)

Top Topics

Top Venues

Lawrence O. Hall