Zobrazeno 91 - 100
of 19 527
pro vyhledávání: '"Liu, Bing"'
Autor:
Luo, Kun, Li, Baozhong, Sun, Lei, Wu, Yingju, Ge, Yanfeng, Liu, Bing, He, Julong, Xu, Bo, Zhao, Zhisheng, Tian, Yongjun
Publikováno v:
Chin. Phys. Lett. 39, 036301 (2022)
Both boron nitride (BN) and carbon (C) have sp, sp2 and sp3 hybridization modes, and thus resulting in a variety of BN and C polymorphs with similar structures, such as hexagonal BN (hBN) and graphite, cubic BN (cBN) and diamond. Here, five types of
Externí odkaz:
http://arxiv.org/abs/2112.14975
Autor:
Guo, Dong, Shi, Yuejiang, Liu, Wenjun, Song, Yunyang, Sun, Tiantian, Liu, Bing, Li, Yingying, Tian, Xiaorang, Zhang, Guosong, Xie, Huasheng, Peng, Y. K. Martin, Liu, Minsheng
Publikováno v:
Plasma Phys. Control. Fusion 64 (2022) 055009 (7pp)
A significant number of confined energetic electrons have been observed outside the Last Closed Flux Surface (LCFS) of the solenoid-free, ECRH sustained plasmas in the EXL-50 spherical torus. Several diagnostics have been applied, for the first time,
Externí odkaz:
http://arxiv.org/abs/2112.10315
Publikováno v:
ECML-PKDD 2020
This paper studies continual learning (CL) for sentiment classification (SC). In this setting, the CL system learns a sequence of SC tasks incrementally in a neural network, where each task builds a classifier to classify the sentiment of reviews of
Externí odkaz:
http://arxiv.org/abs/2112.10021
Publikováno v:
NeurIPS 2020
Existing research on continual learning of a sequence of tasks focused on dealing with catastrophic forgetting, where the tasks are assumed to be dissimilar and have little shared knowledge. Some work has also been done to transfer previously learned
Externí odkaz:
http://arxiv.org/abs/2112.10017
Publikováno v:
NAACL 2021
This paper studies continual learning (CL) of a sequence of aspect sentiment classification (ASC) tasks. Although some CL techniques have been proposed for document sentiment classification, we are not aware of any CL work on ASC. A CL system that in
Externí odkaz:
http://arxiv.org/abs/2112.03271
Publikováno v:
EMNLP 2021
This paper studies continual learning (CL) of a sequence of aspect sentiment classification(ASC) tasks in a particular CL setting called domain incremental learning (DIL). Each task is from a different domain or product. The DIL setting is particular
Externí odkaz:
http://arxiv.org/abs/2112.02714
Publikováno v:
NeurIPS 2021
Continual learning (CL) learns a sequence of tasks incrementally with the goal of achieving two main objectives: overcoming catastrophic forgetting (CF) and encouraging knowledge transfer (KT) across tasks. However, most existing techniques focus onl
Externí odkaz:
http://arxiv.org/abs/2112.02706
Recently, table structure recognition has achieved impressive progress with the help of deep graph models. Most of them exploit single visual cues of tabular elements or simply combine visual cues with other modalities via early fusion to reason thei
Externí odkaz:
http://arxiv.org/abs/2111.13359
The ability of neural networks (NNs) to learn and remember multiple tasks sequentially is facing tough challenges in achieving general artificial intelligence due to their catastrophic forgetting (CF) issues. Fortunately, the latest OWM Orthogonal We
Externí odkaz:
http://arxiv.org/abs/2111.10078
Autor:
Luan, Jixin, Zhang, Di, Liu, Bing, Yang, Aocai, Lv, Kuan, Hu, Pianpian, Yu, Hongwei, Shmuel, Amir, Zhang, Chuanchen, Ma, Guolin
Publikováno v:
In Heliyon 15 July 2024 10(13)