COMPOSE: A Semisupervised Learning Framework for Initially Labeled Nonstationary Streaming Data von Dyer, Karl B., Capo, Robert, Polikar, Robi

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Adversary Aware Continual Learning von Umer, Muhammad, Polikar, Robi

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Machine Learning Analysis of Digital Clock Drawing Test Performance for Differential Classification of Mild Cognitive Impairment Subtypes Versus Alzheimer’s Disease von Binaco, Russell, Calzaretto, Nicholas, Epifano, Jacob, McGuire, Sean, Umer, Muhammad, Emrani, Sheina, Wasserman, Victor, Libon, David J., Polikar, Robi

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Incremental Learning of Concept Drift from Streaming Imbalanced Data von Ditzler, Gregory, Polikar, Robi

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Complet+: a computationally scalable method to improve completeness of large-scale protein sequence clustering von Nguyen, Rachel, Sokhansanj, Bahrad A, Polikar, Robi, Rosen, Gail L

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Incremental Learning of Concept Drift in Nonstationary Environments von Elwell, R., Polikar, R.

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A Sequential Learning Approach for Scaling Up Filter-Based Feature Subset Selection von Ditzler, Gregory, Polikar, Robi, Rosen, Gail

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Guest Editorial Learning in Nonstationary and Evolving Environments von Polikar, Robi, Alippi, Cesare

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Extensions to Online Feature Selection Using Bagging and Boosting von Ditzler, Gregory, LaBarck, Joseph, Ritchie, James, Rosen, Gail, Polikar, Robi

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Identifying amyloid pathology–related cerebrospinal fluid biomarkers for Alzheimer's disease in a multicohort study von Leung, Yuk Yee, Toledo, Jon B, Nefedov, Alexey, Polikar, Robi, Raghavan, Nandini, Xie, Sharon X, Farnum, Michael, Schultz, Tim, Baek, Young, Van Deerlin, Vivianna M, Hu, William T, Holtzman, David M, Fagan, Anne M, Perrin, Richard J, Grossman, Murray, Soares, Holly D, Kling, Mitchel A, Mailman, Matthew, Arnold, Steven E, Narayan, Vaibhav A, Lee, Virginia M-Y, Shaw, Leslie M, Baker, David, Wittenberg, Gayle M, Trojanowski, John Q, Wang, Li-San

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A Bootstrap Based Neyman-Pearson Test for Identifying Variable Importance von Ditzler, Gregory, Polikar, Robi, Rosen, Gail

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Learning from streaming data with concept drift and imbalance: an overview von Hoens, T. Ryan, Polikar, Robi, Chawla, Nitesh V.

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SPECIAL ISSUE ON LEARNING IN NONSTATIONARY AND EVOLVING ENVIRONMENTS von POLIKAR, Robi, ALIPPI, Cesare

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Learn ^ .NC: Combining Ensemble of Classifiers With Dynamically Weighted Consult-and-Vote for Efficient Incremental Learning of New Classes von Muhlbaier, M.D., Topalis, A., Polikar, R.

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Artificial intelligence methods for selection of an optimized sensor array for identification of volatile organic compounds von Polikar, Robi, Shinar, Ruth, Udpa, Lalita, Porter, Marc D.

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Which Is the Best Multiclass SVM Method? An Empirical Study von Duan, Kai-Bo, Keerthi, S. Sathiya

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Signal Processing for Metagenomics: Extracting Information from the Soup von Rosen, Gail L, Sokhansanj, Bahrad A, Polikar, Robi, Bruns, Mary Ann, Russell, Jacob, Garbarine, Elaine, Essinger, Steve, Yok, Non

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COMPOSE: A Semisupervised Learning Framework for Initially Labeled Nonstationary Streaming Data: SPECIAL ISSUE ON LEARNING IN NONSTATIONARY AND EVOLVING ENVIRONMENTS von DYER, Karl B, CAPO, Robert, POLIKAR, Robi

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Learn++: an incremental learning algorithm for supervised neural networks von Polikar, R., Upda, L., Upda, S.S., Honavar, V.

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P50: A candidate ERP biomarker of prodromal Alzheimer's disease von Green, Deborah L, Payne, Lisa, Polikar, Robi, Moberg, Paul J, Wolk, David A, Kounios, John

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