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- Robi Polikar
- IEEE Circuits and Systems Magazine
- 2006

In matters of great importance that have financial, medical, social, or other implications, we often seek a second opinion before making a decision, sometimes a third, and sometimes many more. Inâ€¦ (More)

- Robi Polikar, L. Upda, S. S. Upda, Vasant Honavar
- IEEE Trans. Systems, Man, and Cybernetics, Part C
- 2001

We introduce Learn++, an algorithm for incremental training of neural network (NN) pattern classifiers. The proposed algorithm enables supervised NN paradigms, such as the multilayer perceptronâ€¦ (More)

- Ryan Elwell, Robi Polikar
- IEEE Transactions on Neural Networks
- 2011

We introduce an ensemble of classifiers-based approach for incremental learning of concept drift, characterized by nonstationary environments (NSEs), where the underlying data distributions changeâ€¦ (More)

- Gregory Ditzler, Robi Polikar
- IEEE Transactions on Knowledge and Dataâ€¦
- 2013

Learning in nonstationary environments, also known as learning concept drift, is concerned with learning from data whose statistical characteristics change over time. Concept drift is furtherâ€¦ (More)

- Gregory Ditzler, Robi Polikar
- 2011 IEEE Symposium on Computational Intelligenceâ€¦
- 2011

Most machine learning algorithms, including many online learners, assume that the data distribution to be learned is fixed. There are many real-world problems where the distribution of the dataâ€¦ (More)

- Michael Muhlbaier, Apostolos Topalis, Robi Polikar
- IEEE Transactions on Neural Networks
- 2009

We have previously introduced an incremental learning algorithm Learn++, which learns novel information from consecutive data sets by generating an ensemble of classifiers with each data set, andâ€¦ (More)

- Gregory Ditzler, Manuel Roveri, Cesare Alippi, Robi Polikar
- IEEE Computational Intelligence Magazine
- 2015

The prevalence of mobile phones, the internet-of-things technology, and networks of sensors has led to an enormous and ever increasing amount of data that are now more commonly available in aâ€¦ (More)

- T. Ryan Hoens, Robi Polikar, Nitesh V. Chawla
- Progress in Artificial Intelligence
- 2011

The primary focus of machine learning has traditionally been on learning from data assumed to be sufficient and representative of the underlying fixed, yet unknown, distribution. Such restrictions onâ€¦ (More)

- Karl B. Dyer, Robert Capo, Robi Polikar
- IEEE Transactions on Neural Networks and Learningâ€¦
- 2014

An increasing number of real-world applications are associated with streaming data drawn from drifting and nonstationary distributions that change over time. These applications demand new algorithmsâ€¦ (More)

- Robi Polikar
- Scholarpedia
- 2009