D-Index & Metrics Best Publications

Robi Polikar

Rowan University
United States

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name Citations Publications World Ranking National Ranking

Computer Science D-index 35 Citations 11,196 167 World Ranking 7374 National Ranking 3463

Overview

What is he best known for?

The fields of study Robi Polikar is best known for:

Voting
Machine learning
Artificial neural network

Robi Polikar frequently studies issues relating to Pattern recognition (psychology) and Artificial intelligence. Pattern recognition (psychology) and Artificial intelligence are frequently intertwined in his study. Robi Polikar integrates several fields in his works, including Machine learning and Boosting (machine learning). He integrates Boosting (machine learning) and Ensemble learning in his research. He connects Ensemble learning with Machine learning in his research. Robi Polikar applies his multidisciplinary studies on Artificial neural network and Algorithm in his research. His work often combines Algorithm and Artificial neural network studies. Law connects with themes related to Majority rule in his study. Robi Polikar performs multidisciplinary study on Majority rule and Voting in his works.

His most cited work include:

Ensemble based systems in decision making (2232 citations)
Learn++: an incremental learning algorithm for supervised neural networks (729 citations)

What are the main themes of his work throughout his whole career to date

His Artificial intelligence study frequently draws connections between adjacent fields such as Class (philosophy). His research brings together the fields of Artificial intelligence and Class (philosophy). His Machine learning study frequently links to adjacent areas such as Incremental learning. His Machine learning research extends to the thematically linked field of Incremental learning. Robi Polikar performs integrative study on Pattern recognition (psychology) and Forgetting. Robi Polikar connects Forgetting with Pattern recognition (psychology) in his study. His Classifier (UML) study frequently draws connections to other fields, such as Random subspace method. His studies link Classifier (UML) with Random subspace method. Robi Polikar performs multidisciplinary studies into Algorithm and Computation in his work.

Robi Polikar most often published in these fields:

Artificial intelligence (78.57%)
Machine learning (57.14%)
Pattern recognition (psychology) (50.00%)

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