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pro vyhledávání: '"Jiang, Penghao"'
Autor:
Yan, Ruiqing, Du, Xingbo, Deng, Haoyu, Zheng, Linghan, Sun, Qiuzhuang, Hu, Jifang, Shao, Yuhang, Jiang, Penghao, Jiang, Jinrong, Zhao, Lian
With the advent of large models based on the Transformer architecture, researchers have observed an anomalous phenomenon in the Attention mechanism--there is a very high attention on the first element, which is prevalent across Transformer-based mode
Externí odkaz:
http://arxiv.org/abs/2407.01601
Document-based Visual Question Answering poses a challenging task between linguistic sense disambiguation and fine-grained multimodal retrieval. Although there has been encouraging progress in document-based question answering due to the utilization
Externí odkaz:
http://arxiv.org/abs/2310.07091
Unsupervised pre-training approaches have achieved great success in many fields such as Computer Vision (CV), Natural Language Processing (NLP) and so on. However, compared to typical deep learning models, pre-training or even fine-tuning the state-o
Externí odkaz:
http://arxiv.org/abs/2302.10820
This paper studies the data sparsity problem in multi-view learning. To solve data sparsity problem in multiview ratings, we propose a generic architecture of deep transfer tensor factorization (DTTF) by integrating deep learning and cross-domain ten
Externí odkaz:
http://arxiv.org/abs/2302.06133
A machine learning model that generalizes well should obtain low errors on unseen test examples. Thus, if we learn an optimal model in training data, it could have better generalization performance in testing tasks. However, learning such a model is
Externí odkaz:
http://arxiv.org/abs/2301.12698
Modern deep learning techniques have illustrated their excellent capabilities in many areas, but relies on large training data. Optimization-based meta-learning train a model on a variety tasks, such that it can solve new learning tasks using only a
Externí odkaz:
http://arxiv.org/abs/2301.11779
Publikováno v:
In Progress in Nuclear Energy April 2023 158
Autor:
Zhang, Mengzhou, Zhang, Miao, Wang, Linlin, Yu, Tianshui, Jiang, Shukun, Jiang, Penghao, Sun, Yingfu, Pi, Jingbo, Zhao, Rui, Guan, Dawei
Publikováno v:
In Life Sciences 1 August 2019 230:55-67
Publikováno v:
网络与信息安全学报, Vol 4, Iss 9, Pp 17-22 (2018)
With the diversified development of the current network,users’ demand grows as well which brings great challenge for its load ability.A QLearning based business differentiating routing mechanism in SDN architecture was proposed to guarantee users
Externí odkaz:
https://doaj.org/article/e67247697dea4d7f9910ff56067cb9c0
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