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arXiv:2405.15824v1 Announce Type: new Abstract: Curriculum learning has been growing in the domain of reinforcement learning as a method of improving training efficiency for various tasks. It involves modifying the difficulty (lessons) of the environment as the agent learns, in order to encourage more optimal agent behavior and higher reward states. However, most curriculum learning methods currently involve discrete transitions of the curriculum or predefined steps by the programmer or using automatic curriculum learning on only a small subset training such as only on an adversary. In this paper, we propose a novel approach to curriculum learning that uses a…

[Submitted on 17 Apr 2024] Authors:Aristeidis Tsaris, Chengming Zhang, Xiao Wang, Junqi Yin, Siyan Liu, Moetasim Ashfaq, Ming Fan, Jong Youl Choi, Mohamed Wahib, Dan Lu, Prasanna Balaprakash, Feiyi Wang View a PDF of the paper titled Sequence Length Scaling in Vision Transformers for Scientific Images on Frontier, by Aristeidis Tsaris and 11 other authors View PDF Abstract:Vision Transformers (ViTs) are pivotal for foundational models in scientific imagery, including Earth science applications, due to their capability to process large sequence lengths. While transformers for text has inspired scaling sequence lengths in ViTs, yet adapting these for ViTs introduces unique challenges.…

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