( en | de | ru )

 

Disambiguation of "Polikar, Robi"

Author of the publication

copydeleteadd this publication to your clipboard
Incremental Learning of Concept Drift from Streaming Imbalanced Data.

, and . IEEE Trans. Knowl. Data Eng., 25 (10): 2283-2301 (2013)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

Robi Malik

Robi Banerjee

Robi Banerjee

Gerhard Röbisch

Nehemia Robinson

 

Other publications of authors with the same name

Adversarial Poisoning of Importance Weighting in Domain Adaptation., , and . SSCI, page 381-388. IEEE, (2018)Incremental Learning of Concept Drift in Nonstationary Environments., and . IEEE Trans. Neural Networks, 22 (10): 1517-1531 (2011)Classification of Volatile Organic Compounds with Incremental SVMs and RBF Networks., , , and . ISCIS, volume 3733 of Lecture Notes in Computer Science, page 322-331. Springer, (2005)A Sequential Learning Approach for Scaling Up Filter-Based Feature Subset Selection., , and . IEEE Trans. Neural Networks Learn. Syst., 29 (6): 2530-2544 (2018)Semi-supervised learning in initially labeled non-stationary environments with gradual drift., and . IJCNN, page 1-9. IEEE, (2012)Core support extraction for learning from initially labeled nonstationary environments using COMPOSE., , and . IJCNN, page 602-608. IEEE, (2014)Incremental Learning of Concept Drift from Streaming Imbalanced Data., and . IEEE Trans. Knowl. Data Eng., 25 (10): 2283-2301 (2013)An architecture for intelligent systems based on smart sensors., , , , and . IEEE Trans. Instrumentation and Measurement, 54 (4): 1612-1616 (2005)Can AdaBoost.M1 Learn Incrementally? A Comparison to Learn++ Under Different Combination Rules., , , and . ICANN (1), volume 4131 of Lecture Notes in Computer Science, page 254-263. Springer, (2006)Incremental and Semi-Supervised Learning of 16S-rRNA Genes For Taxonomic Classification., , , , , , , , , and . SSCI, page 1-7. IEEE, (2021)