( en | de | ru )

 

Disambiguation of "Cho, Sung-Bae"

Author of the publication

copydeleteadd this publication to your clipboard
Effective Rule Discovery Using Genetic Programming for DNA Microarray Analysis

, and . Proceedings of The First Asian-Pacific Workshop on Genetic Programming, page 53--61. Rydges (lakeside) Hotel, Canberra, Australia, (8 December 2003)

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.

Sung Bae Kim

Sung-Min Bae

Sung-Jun Cho

Sung-bok Cho

Gyu-Sung Cho

 

Other publications of authors with the same name

Autonomous Language Development Using Dialogue-Act Templates and Genetic Programming, , and . IEEE Transactions on Evolutionary Computation, 11 (2): 213--225 (April 2007)Evolutionary Learning of Modular Neural Networks with Genetic Programming, and . Applied Intelligence, 9 (3): 191--200 (November 1998)Adaptive Behavior of Incrementally Evolved Neural Networks based on Cellular Automata, and . Proceedings of the Genetic and Evolutionary Computation Conference, 2, page 1449. Orlando, Florida, USA, Morgan Kaufmann, (13-17 July 1999)Generative Adversarial Network with Guided Generator for Non-stationary Noise Cancelation., , and . HAIS, volume 12344 of Lecture Notes in Computer Science, page 3-12. Springer, (2020)Strategic Application of Feedforward Neural Networks to Large-Scale Classification., and . Complex Syst., (1992)A Dining Context-Aware System with Mobile and Wearable Devices., and . CIT/IUCC/DASC/PICom, page 2381-2386. IEEE, (2015)Unsupervised Functional Link Artificial Neural Networks for Cluster Analysis., , , and . IEEE Access, (2020)Cross-Domain Fault Diagnosis of Rotating Machinery Using Discriminative Feature Attention Network., , and . IEEE Access, (2021)Cybersecurity applications of computational intelligence., , , , and . Neural Comput. Appl., 34 (23): 20447-20448 (2022)Learning Disentangled Representation of Residential Power Demand Peak via Convolutional-Recurrent Triplet Network., , and . ICDM (Workshops), page 757-761. IEEE, (2020)