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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 32

Active Lifelong Learning With “Watchdog”

March 15, 2023

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Published Date: 2018-02-08

Registration: ISSN 2374-3468 (Online) ISSN 2159-5399 (Print)

Copyright: Published by AAAI Press, Palo Alto, California USA Copyright © 2018, Association for the Advancement of Artificial Intelligence All Rights Reserved.

Authors

Gan Sun

Shenyang Institute of Automation, Chinese Academy of Sciences; University of Chinese Academy of Sciences


Yang Cong

Shenyang Institute of Automation, Chinese Academy of Sciences


Xiaowei Xu

University of Arkansas at Little Rock


DOI:

10.1609/aaai.v32i1.11705


Abstract:

Lifelong learning intends to learn new consecutive tasks depending on previously accumulated experiences, i.e., knowledge library. However, the knowledge among different new coming tasks are imbalance. Therefore, in this paper, we try to mimic an effective "human cognition" strategy by actively sorting the importance of new tasks in the process of unknown-to-known and selecting to learn the important tasks with more information preferentially. To achieve this, we consider to assess the importance of the new coming task, i.e., unknown or not, as an outlier detection issue, and design a hierarchical dictionary learning model consisting of two-level task descriptors to sparse reconstruct each task with the l0 norm constraint. The new coming tasks are sorted depending on the sparse reconstruction score in descending order, and the task with high reconstruction score will be permitted to pass, where this mechanism is called as "watchdog." Next, the knowledge library of the lifelong learning framework encode the selected task by transferring previous knowledge, and then can also update itself with knowledge from both previously learned task and current task automatically. For model optimization, the alternating direction method is employed to solve our model and converges to a fixed point. Extensive experiments on both benchmark datasets and our own dataset demonstrate the effectiveness of our proposed model especially in task selection and dictionary learning.

Topics: AAAI

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HOW TO CITE:

Gan Sun||Yang Cong||Xiaowei Xu Active Lifelong Learning With “Watchdog” Proceedings of the AAAI Conference on Artificial Intelligence, 32 (2018) .

Gan Sun||Yang Cong||Xiaowei Xu Active Lifelong Learning With “Watchdog” AAAI 2018, .

Gan Sun||Yang Cong||Xiaowei Xu (2018). Active Lifelong Learning With “Watchdog”. Proceedings of the AAAI Conference on Artificial Intelligence, 32, .

Gan Sun||Yang Cong||Xiaowei Xu. Active Lifelong Learning With “Watchdog”. Proceedings of the AAAI Conference on Artificial Intelligence, 32 2018 p..

Gan Sun||Yang Cong||Xiaowei Xu. 2018. Active Lifelong Learning With “Watchdog”. "Proceedings of the AAAI Conference on Artificial Intelligence, 32". .

Gan Sun||Yang Cong||Xiaowei Xu. (2018) "Active Lifelong Learning With “Watchdog”", Proceedings of the AAAI Conference on Artificial Intelligence, 32, p.

Gan Sun||Yang Cong||Xiaowei Xu, "Active Lifelong Learning With “Watchdog”", AAAI, p., 2018.

Gan Sun||Yang Cong||Xiaowei Xu. "Active Lifelong Learning With “Watchdog”". Proceedings of the AAAI Conference on Artificial Intelligence, 32, 2018, p..

Gan Sun||Yang Cong||Xiaowei Xu. "Active Lifelong Learning With “Watchdog”". Proceedings of the AAAI Conference on Artificial Intelligence, 32, (2018): .

Gan Sun||Yang Cong||Xiaowei Xu. Active Lifelong Learning With “Watchdog”. AAAI[Internet]. 2018[cited 2023]; .


ISSN: 2374-3468


Published by AAAI Press, Palo Alto, California USA
Copyright 2022, Association for the Advancement of
Artificial Intelligence 1900 Embarcadero Road, Suite
101, Palo Alto, California 94303 All Rights Reserved

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