Continual Learning Algorithms Inspired by Human Learning, M.Sc. Thesis Sharif University of Technology ; Soleymani Baghshah, Mahdieh (Supervisor)
Abstract
Despite the remarkable success of deep learning algorithms in recent years, it still has a long way to reach the status of human natural intelligence and to acquire the expected self-autonomy. As a result, many researchers in this field have focused on the development of these algorithms while taking inspiration from human cognitive behaviors. One of the disadvantages of current algorithms is the lack of their ability to learn in a continual manner while deployed in the environment. More precisely, deep learning models are not able to gradually gather knowledge from the environment and if they are in a situation of limited access to data, they will suffer from catastrophic forgetting; a...
Cataloging briefContinual Learning Algorithms Inspired by Human Learning, M.Sc. Thesis Sharif University of Technology ; Soleymani Baghshah, Mahdieh (Supervisor)
Abstract
Despite the remarkable success of deep learning algorithms in recent years, it still has a long way to reach the status of human natural intelligence and to acquire the expected self-autonomy. As a result, many researchers in this field have focused on the development of these algorithms while taking inspiration from human cognitive behaviors. One of the disadvantages of current algorithms is the lack of their ability to learn in a continual manner while deployed in the environment. More precisely, deep learning models are not able to gradually gather knowledge from the environment and if they are in a situation of limited access to data, they will suffer from catastrophic forgetting; a...
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