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2020 19th IEEE International Conference on Machine Learning and Applications (ICMLA) by Witzgall, Hanna (author) is a nonfiction available to read on EtoBox.

What is 2020 19th IEEE International Conference on Machine Learning and Applications (ICMLA) about?

The amount of time required to train most deep neural networks makes them ill-suited for continuous learning applications where one would like to augment existing models with new classes on-the-edge and on-the-fly. This paper presents a new type of progressive learning approach called Rapid Class Augmentation (RCA) that can be used to rapidly augment an existing classifier with new classes. RCA has the distinguishing properties of optimizer feature memory and a class initialization vector that enable it to train on only the new class examples while optimally updating all the model's classification weights. This paper will demonstrate that these properties allow RCA to augment existing models much faster and with reduced data storage requirements than conventional progressive learning techniques that rely on stochastic gradient descent optimization. This rapid class augmentation capability is expected to be especially advantageous for near real-time perception tasks that require continuous learning of new network classes on platforms with limited data storage and compute power.

Who reads 2020 19th IEEE International Conference on Machine Learning and Applications (ICMLA)?

Author

Witzgall, Hanna (author)

Publisher

IEEE

Published

2020

Language

EN

Category

nonfiction