Lawrence O. Hall

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 Recognition 46(3): 692-702 (2013)

Juana Canul-Reich, Lawrence O. Hall, Dmitry B. Goldgof, John N. Korecki, Steven Eschrich: Iterative Feature perturbation as a gene Selector for microarray Data. IJPRAI 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 T. Fuzzy Systems 20(6): 1130-1146 (2012)

Lawrence O. Hall: Objective function-based clustering. Wiley Interdisc. Rew.: Data Mining and Knowledge Discovery 2(4): 326-339 (2012)

Jonathon K. Parker, Lawrence O. Hall, James C. Bezdek: Comparison of scalable fuzzy clustering methods. FUZZ-IEEE 2012: 1-9

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: 3504-3508

Lawrence O. Hall: Exploring Big Data with Scalable Soft Clustering. SMPS 2012: 11-15

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): 259-290 (2011)

Lawrence O. Hall, Dmitry B. Goldgof: Convergence of the Single-Pass and Online Fuzzy C-Means Algorithms. IEEE T. Fuzzy Systems 19(4): 792-794 (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: 318-324

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: 741-748

Larry Shoemaker, Lawrence O. Hall: Anomaly Detection Using Ensembles. MCS 2011: 6-15

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: 909-913

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: 1306-1312

Kevin W. Bowyer, Nitesh V. Chawla, Lawrence O. Hall, W. Philip Kegelmeyer: SMOTE: Synthetic Minority Over-sampling Technique. CoRR abs/1106.1813 (2011)

Lawrence O. Hall, Dmitry B. Goldgof: On convergence properties of the singlepass and online fuzzy c-means algorithm. FUZZ-IEEE 2010: 1-3

Jonathon K. Parker, Lawrence O. Hall, Abraham Kandel: Scalable fuzzy neighborhood DBSCAN. FUZZ-IEEE 2010: 1-8

Yuhua Gu, Lawrence O. Hall, Dmitry B. Goldgof: Evaluating scalable fuzzy clustering. SMC 2010: 873-880

Juana Canul-Reich, Lawrence O. Hall, Dmitry B. Goldgof, Steven Eschrich: Filtering for improved gene selection on microarray data. SMC 2010: 3250-3257

Prodip Hore, Lawrence O. Hall, Dmitry B. Goldgof: A scalable framework for cluster ensembles. Pattern Recognition 42(5): 676-688 (2009)

Kurt Kramer, Lawrence O. Hall, Dmitry B. Goldgof, Andrew Remsen, Tong Luo: Fast Support Vector Machines for Continuous Data. IEEE Transactions on Systems, Man, and Cybernetics, Part B 39(4): 989-1001 (2009)

Prodip Hore, Lawrence O. Hall, Dmitry B. Goldgof, Yuhua Gu, Andrew Maudsley, Ammar Darkazanli: A Scalable Framework For Segmenting Magnetic Resonance Images. Signal Processing Systems 54(1-3): 183-203 (2009)

Yuhua Gu, Lawrence O. Hall, Dmitry B. Goldgof: Ant Clustering Using Ensembles of Partitions. MCS 2009: 283-292

Weijian Cheng, Lawrence O. Hall, Dmitry B. Goldgof, Chuanmin Hu, Inia M. Soto: Automatic Red Tide Detection from MODIS Satellite Images. SMC 2009: 1864-1868

Nitesh V. Chawla, David A. Cieslak, Lawrence O. Hall, Ajay Joshi: Automatically countering imbalance and its empirical relationship to cost. Data Min. Knowl. Discov. 17(2): 225-252 (2008)

Larry Shoemaker, Robert E. Banfield, Lawrence O. Hall, Kevin W. Bowyer, W. Philip Kegelmeyer: Using classifier ensembles to label spatially disjoint data. Information Fusion 9(1): 120-133 (2008)

Juana Canul-Reich, Lawrence O. Hall, Dmitry B. Goldgof, Steven Eschrich: Feature selection for microarray data by AUC analysis. SMC 2008: 768-773

Robert E. Banfield, Lawrence O. Hall, Kevin W. Bowyer, W. Philip Kegelmeyer: A Comparison of Decision Tree Ensemble Creation Techniques. IEEE Trans. Pattern Anal. Mach. Intell. 29(1): 173-180 (2007)

Parag M. Kanade, Lawrence O. Hall: Fuzzy Ants and Clustering. IEEE Transactions on Systems, Man, and Cybernetics, Part A 37(5): 758-769 (2007)

Vidya P. Kamath, Lawrence O. Hall, Timothy Yeatman, Steven Eschrich: Multivariate Feature Selection using Random Subspace Classifiers for Gene Expression Data. BIBE 2007: 1041-1045

Juana Canul-Reich, Larry Shoemaker, Lawrence O. Hall: Ensembles of Fuzzy Classifiers. FUZZ-IEEE 2007: 1-6

Prodip Hore, Lawrence O. Hall, Dmitry B. Goldgof: Single Pass Fuzzy C Means. FUZZ-IEEE 2007: 1-7

Li Chen, Dmitry B. Goldgof, Lawrence O. Hall, Steven Eschrich: Noise-Based Feature Perturbation as a Selection Method for Microarray Data. ISBRA 2007: 237-247

Lawrence O. Hall, Robert E. Banfield, Kevin W. Bowyer, W. Philip Kegelmeyer: Boosting Lite - Handling Larger Datasets and Slower Base Classifiers. MCS 2007: 161-170

Prodip Hore, Lawrence O. Hall, Dmitry B. Goldgof: A fuzzy c means variant for clustering evolving data streams. SMC 2007: 360-365

Sergiy Fefilatyev, Tim V. Ivanovskiy, Lawrence O. Hall, Dmitry B. Goldgof, Shibendra S. Pobi, Halina Greenstien, Amit P. Pathak, Christopher R. Garret: Clinical deployment of a medical expert system to increase accruals for clinical trials: Challenges. SMC 2007: 1482-1487

Yong Zhang, Lawrence O. Hall, Dmitry B. Goldgof, Sudeep Sarkar: A constrained genetic approach for computing material property of elastic objects. IEEE Trans. Evolutionary Computation 10(3): 341-357 (2006)

Sergiy Fefilatyev, Volha Smarodzinava, Lawrence O. Hall, Dmitry B. Goldgof: Horizon Detection Using Machine Learning Techniques. ICMLA 2006: 17-21

Cindy L. Bethel, Lawrence O. Hall, Dmitry B. Goldgof: Mining for Implications in Medical Data. ICPR (1) 2006: 1212-1215

Larry Shoemaker, Robert E. Banfield, Lawrence O. Hall, Kevin W. Bowyer, W. Philip Kegelmeyer: Learning to Predict Salient Regions from Disjoint and Skewed Training Sets. ICTAI 2006: 116-126

Shibendra S. Pobi, Lawrence O. Hall: Predicting Juvenile Diabetes from Clinical Test Results. IJCNN 2006: 2159-2165

Prodip Hore, Lawrence O. Hall, Dmitry B. Goldgof: A Cluster Ensemble Framework for Large Data sets. SMC 2006: 3342-3347

Robert E. Banfield, Lawrence O. Hall, Kevin W. Bowyer, W. Philip Kegelmeyer: Ensemble diversity measures and their application to thinning. Information Fusion 6(1): 49-62 (2005)

Tong Luo, Kurt Kramer, Dmitry B. Goldgof, Lawrence O. Hall, Scott Samson, Andrew Remsen, Thomas Hopkins: Active Learning to Recognize Multiple Types of Plankton. Journal of Machine Learning Research 6: 589-613 (2005)

Lawrence O. Hall, Parag M. Kanade: Scalable Swarm Based Fuzzy Clustering. GfKl 2005: 21-31

Tong Luo, Lawrence O. Hall, Dmitry B. Goldgof, Andrew Remsen: Bit Reduction Support Vector Machine. ICDM 2005: 733-736

Robert E. Banfield, Lawrence O. Hall, Kevin W. Bowyer, W. Philip Kegelmeyer: Ensembles of Classifiers from Spatially Disjoint Data. Multiple Classifier Systems 2005: 196-205

Yuhua Gu, Lawrence O. Hall, Dmitry B. Goldgof, Parag M. Kanade, F. Reed Murtagh: Sequence tolerant segmentation system of brain MRI. SMC 2005: 2936-2943

Eugene Fink, Princeton K. Kokku, Savvas Nikiforou, Lawrence O. Hall, Dmitry B. Goldgof, Jeffrey P. Krischer: Selection of patients for clinical trials: an interactive web-based system. Artificial Intelligence in Medicine 31(3): 241-254 (2004)

Nitesh V. Chawla, Lawrence O. Hall, Kevin W. Bowyer, W. Philip Kegelmeyer: Learning Ensembles from Bites: A Scalable and Accurate Approach. Journal of Machine Learning Research 5: 421-451 (2004)

Xiaomei Liu, Lawrence O. Hall, Kevin W. Bowyer: Comments on "A Parallel Mixture of SVMs for Very Large Scale Problems". Neural Computation 16(7): 1345-1351 (2004)

Tong Luo, Kurt Kramer, Dmitry B. Goldgof, Lawrence O. Hall, Scott Samson, Andrew Remsen, Thomas Hopkins: Recognizing plankton images from the shadow image particle profiling evaluation recorder. IEEE Transactions on Systems, Man, and Cybernetics, Part B 34(4): 1753-1762 (2004)

Tong Luo, Kurt Kramer, Dmitry B. Goldgof, Lawrence O. Hall, Scott Samson, Andrew Remsen, Thomas Hopkins: Errata to "Recognizing Plankton Images From the Shadow Image Particle Profiling Evaluation Recorder". IEEE Transactions on Systems, Man, and Cybernetics, Part B 34(6): 2423-2423 (2004)

Lawrence O. Hall: List of Reviewers. IEEE Transactions on Systems, Man, and Cybernetics, Part B 34(6): 2486-2491 (2004)

Bhavesh D. Goswami, Lawrence O. Hall, Dmitry B. Goldgof, Eugene Fink, Jeffrey P. Krischer: Using Probabilistic Methods to Optimize Data Entry in Accrual of Patients to Clinical Trials. CBMS 2004: 434-

Tong Luo, Kurt Kramer, Dmitry B. Goldgof, Lawrence O. Hall, Scott Samson, Andrew Remsen, Thomas Hopkins: Active Learning to Recognize Multiple Types of Plankton. ICPR (3) 2004: 478-481

Robert E. Banfield, Lawrence O. Hall, Kevin W. Bowyer, Divya Bhadoria, W. Philip Kegelmeyer, Steven Eschrich: A Comparison of Ensemble Creation Techniques. Multiple Classifier Systems 2004: 223-232

Lawrence O. Hall, Divya Bhadoria, Kevin W. Bowyer: Learning a model from spatially disjoint data. SMC (2) 2004: 1447-1451

Xiaomei Liu, Kevin W. Bowyer, Lawrence O. Hall: Decision trees work better than feed-forward back-prop neural nets for a specific class of problems. SMC (6) 2004: 5969-5974

Lawrence O. Hall, Kevin W. Bowyer, Robert E. Banfield, Steven Eschrich, Richard Collins: Is Error-Based Pruning Redeemable? International Journal on Artificial Intelligence Tools 12(3): 249-264 (2003)

Nitesh V. Chawla, Thomas E. Moore, Lawrence O. Hall, Kevin W. Bowyer, W. Philip Kegelmeyer, Clayton Springer: Distributed learning with bagging-like performance. Pattern Recognition Letters 24(1-3): 455-471 (2003)

Steven Eschrich, Jingwei Ke, Lawrence O. Hall, Dmitry B. Goldgof: Fast accurate fuzzy clustering through data reduction. IEEE T. Fuzzy Systems 11(2): 262-270 (2003)

Michael R. Berthold, Lawrence O. Hall: Visualizing fuzzy points in parallel coordinates. IEEE T. Fuzzy Systems 11(3): 369-374 (2003)

Lawrence O. Hall, Kevin W. Bowyer, Robert E. Banfield, Divya Bhadoria, W. Philip Kegelmeyer, Steven Eschrich: Comparing Pure Parallel Ensemble Creation Techniques Against Bagging. ICDM 2003: 533-536

Robert E. Banfield, Lawrence O. Hall, Kevin W. Bowyer, W. Philip Kegelmeyer: A New Ensemble Diversity Measure Applied to Thinning Ensembles. Multiple Classifier Systems 2003: 306-316

Nitesh V. Chawla, Aleksandar Lazarevic, Lawrence O. Hall, Kevin W. Bowyer: SMOTEBoost: Improving Prediction of the Minority Class in Boosting. PKDD 2003: 107-119

Tong Luo, Kurt Kramer, Dmitry B. Goldgof, Lawrence O. Hall, Scott Samson, Andrew Remsen, Thomas Hopkins: Learning to recognize plankton. SMC 2003: 888-893

Lawrence O. Hall, Xiaomei Liu, Kevin W. Bowyer, Robert E. Banfield: Why are neural networks sometimes much more accurate than decision trees: an analysis on a bio-informatics problem. SMC 2003: 2851-2856

Eugene Fink, Lawrence O. Hall, Dmitry B. Goldgof, Bhavesh D. Goswami, Matthew Boonstra, Jeffrey P. Krischer: Experiments on the automated selection of patients for clinical trials. SMC 2003: 4541-4545

Nitesh V. Chawla, Kevin W. Bowyer, Lawrence O. Hall, W. Philip Kegelmeyer: SMOTE: Synthetic Minority Over-sampling Technique. J. Artif. Intell. Res. (JAIR) 16: 321-357 (2002)

Mingrui Zhang, Lawrence O. Hall, Dmitry B. Goldgof: A generic knowledge-guided image segmentation and labeling system using fuzzy clustering algorithms. IEEE Transactions on Systems, Man, and Cybernetics, Part B 32(5): 571-582 (2002)

Lawrence O. Hall, Richard Collins, Kevin W. Bowyer, Robert E. Banfield: Error-Based Pruning of Decision Trees Grown on Very Large Data Sets Can Work! ICTAI 2002: 233-238

Steven Eschrich, Nitesh V. Chawla, Lawrence O. Hall: Generalization Methods in Bioinformatics. BIOKDD 2002: 25-32

Nitesh V. Chawla, Lawrence O. Hall, Kevin W. Bowyer, Thomas E. Moore, W. Philip Kegelmeyer: Distributed Pasting of Small Votes. Multiple Classifier Systems 2002: 52-61

Lynn M. Fletcher-Heath, Lawrence O. Hall, Dmitry B. Goldgof, F. Reed Murtagh: Automatic segmentation of non-enhancing brain tumors in magnetic resonance images. Artificial Intelligence in Medicine 21(1-3): 43-63 (2001)

Horia-Nicolai L. Teodorescu, Abraham Kandel, Lawrence O. Hall: Report of research activities in fuzzy AI and medicine at USF CSE. Artificial Intelligence in Medicine 21(1-3): 177-183 (2001)

Lawrence O. Hall: Rule chaining in fuzzy expert systems. IEEE T. Fuzzy Systems 9(6): 822-828 (2001)

K. Patipati, Lawrence O. Hall: SMCB goes all electronic. IEEE Transactions on Systems, Man, and Cybernetics, Part B 31(4): 481 (2001)

Nitesh V. Chawla, Thomas E. Moore, Kevin W. Bowyer, Lawrence O. Hall, Clayton Springer, W. Philip Kegelmeyer: Bagging Is a Small-Data-Set Phenomenon. CVPR (2) 2001: 684-689

T. Perroud, Karin Sobottka, Horst Bunke, Lawrence O. Hall: Text Extraction from Color Documents - Clustering Approaches in Three and Four Dimensions. ICDAR 2001: 937-941

Nitesh V. Chawla, Steven Eschrich, Lawrence O. Hall: Creating Ensembles of Classifiers. ICDM 2001: 580-581

Nitesh V. Chawla, Thomas E. Moore, Kevin W. Bowyer, Lawrence O. Hall, Clayton Springer, W. Philip Kegelmeyer: Investigation of bagging-like effects and decision trees versus neural nets in protein secondary structure prediction. BIOKDD 2001: 50-59

Mingrui Zhang, Lawrence O. Hall, Dmitry B. Goldgof, Frank E. Müller-Karger: Knowledge-Guided Classification of Coastal Zone Color Images Off the West Florida Shelf. IJPRAI 14(8): 987-1007 (2000)

Wensheng Yao, Lawrence O. Hall, Dmitry B. Goldgof, Frank E. Müller-Karger: Finding Green River in SeaWiFS Satellite Images. ICPR 2000: 2307-2310

Lawrence O. Hall, Ibrahim Burak Özyurt, James C. Bezdek: Clustering with a genetically optimized approach. IEEE Trans. Evolutionary Computation 3(2): 103-112 (1999)

Ibrahim Burak Özyurt, Lawrence O. Hall, Aydin K. Sunol: SQFDiag: semi-quantitative model-based fault monitoring and diagnosis via episodic fuzzy rules. IEEE Transactions on Systems, Man, and Cybernetics, Part A 29(3): 294-306 (1999)

Lawrence O. Hall, Nitesh V. Chawla, Kevin W. Bowyer, W. Philip Kegelmeyer: Learning Rules from Distributed Data. Large-Scale Parallel Data Mining 1999: 211-220

Lawrence O. Hall, Petter Lande: Generation of Fuzzy Rules from Decision Trees. JACIII 2(4): 128-133 (1998)

Matthew C. Clark, Lawrence O. Hall, Dmitry B. Goldgof, Robert P. Velthuizen, F. Reed Murtagh, Martin L. Silbiger: Automatic Tumor Segmentation Using Knowledge-Based Clustering. IEEE Trans. Med. Imaging 17(2): 187-201 (1998)

Sanjukta Bhanja, Lynn M. Fletcher-Heath, Lawrence O. Hall, Dmitry B. Goldgof, Jeffrey P. Krischer: A Qualitative Expert System for Clinical Trial Assignment. FLAIRS Conference 1998: 84-88

Ibrahim Burak Özyurt, Aydin K. Sunol, Lawrence O. Hall: Chemical Process Fault Diagnosis Using Kernel Retrofitted Fuzzy Genetic Algorithm Based Learner (FGAL) with a Hidden Markov Model. IEA/AIE (Vol. 1) 1998: 190-199

Robert P. Velthuizen, Lawrence O. Hall, Laurence P. Clarke, Martin L. Silbiger: An investigation of mountain method clustering for large data sets. Pattern Recognition 30(7): 1121-1135 (1997)

Amine Bensaid, Lawrence O. Hall, James C. Bezdek, Laurence P. Clarke: Partially supervised clustering for image segmentation. Pattern Recognition 29(5): 859-871 (1996)

Lawrence O. Hall, Richard J. Hathaway: Fuzzy Systems Toolbox, Fuzzy Logic Toolbox [Software Review]. IEEE T. Fuzzy Systems 4(1): 82 (1996)

Amine Bensaid, Lawrence O. Hall, James C. Bezdek, Laurence P. Clarke, Martin L. Silbiger, John A. Arrington, F. Reed Murtagh: Validity-guided (re)clustering with applications to image segmentation. IEEE T. Fuzzy Systems 4(2): 112-123 (1996)

Kevin S. Woods, Diane J. Cook, Lawrence O. Hall, Kevin W. Bowyer, Louise Stark: Learning Membership Functions in a Function-Based Object Recognition System. J. Artif. Intell. Res. (JAIR) 3: 187-222 (1995)

Matthew C. Clark, Lawrence O. Hall, Dmitry B. Goldgof, Martin L. Silbiger: Using Fuzzy Information in Knowledge Guided Segmentation of Brain Tumors. Fuzzy Logic in Artificial Intelligence 1995: 167-181

James C. Bezdek, Srinivas Boggavarapu, Lawrence O. Hall, Amine Bensaid: Genetic Algorithm Guided Clustering. International Conference on Evolutionary Computation 1994: 34-39

Louise Stark, Lawrence O. Hall, Kevin W. Bowyer: Methods for Combination of Evidence in Function-Based 3-D Object Recognition. IJPRAI 7(3): 573-594 (1993)

Steve G. Romaniuk, Lawrence O. Hall: SC-net: A hybrid connectionist, symbolic system. Inf. Sci. 71(3): 223-268 (1993)

Kevin S. Woods, Diane J. Cook, Lawrence O. Hall, Louise Stark, Kevin W. Bowyer: Learning Fuzzy Membership Functions in a Function-Based Object Recognition System. Fuzzy Logic in Artificial Intelligence 1993: 77-96

Lawrence O. Hall: Backpac: A parallel goal-driven reasoning system. Inf. Sci. 62(1-2): 169-182 (1992)

Katsuaki Sanou, Steve G. Romaniuk, Lawrence O. Hall: A Hybrid/Symbolic Connectionist Production System. ICTAI 1992: 44-53

Lawrence O. Hall, Steve G. Romaniuk: A Hybrid Connectionist, Symbolic Learning System. AAAI 1990: 783-788

Lawrence O. Hall: On the choice of ply operators for modus ponens generation in fuzzy intelligent systems. Int. J. Approx. Reasoning 2(2): 101 (1988)

Lawrence O. Hall, Sue Szabo, Abraham Kandel: On the derivation of memberships for fuzzy sets in expert systems. Inf. Sci. 40(1): 39-52 (1986)

Lawrence O. Hall, Wyllis Bandler, Abraham Kandel: New Concepts for Expert Systems Capable of Intelligence in an Imprecise Environment. IAS 1986: 246-250

Lawrence O. Hall, Wyllis Bandler: Relational Knowledge Acquisition. CAIA 1985: 509-513