Zobrazeno 1 - 10
of 1 830
pro vyhledávání: '"XIONG, Liang"'
Autor:
Zhang, Tunhou, Cheng, Dehua, He, Yuchen, Chen, Zhengxing, Dai, Xiaoliang, Xiong, Liang, Liu, Yudong, Cheng, Feng, Cao, Yufan, Yan, Feng, Li, Hai, Chen, Yiran, Wen, Wei
Publikováno v:
ACM Transactions on Recommender Systems (TORS) 2024
The increasing popularity of deep learning models has created new opportunities for developing AI-based recommender systems. Designing recommender systems using deep neural networks requires careful architecture design, and further optimization deman
Externí odkaz:
http://arxiv.org/abs/2411.07569
Autor:
Xiong, Liang, Liu, Jianzhou
Multipartite quantum scenarios are a significant and challenging resource in quantum information science. Tensors provide a powerful framework for representing multipartite quantum systems. In this work, we introduce the role of tensor-generated matr
Externí odkaz:
http://arxiv.org/abs/2410.18592
Autor:
Xiong, Liang, Sze, Nung-Sing
Separability from the spectrum is a significant and ongoing research topic in quantum entanglement. In this study, we investigate properties related to absolute separability from the spectrum in qudits-qudits states in the bipartite states space $\ma
Externí odkaz:
http://arxiv.org/abs/2408.11684
Autor:
Rangadurai, Kaushik, Yuan, Siyang, Huang, Minhui, Liu, Yiqun, Ghasemiesfeh, Golnaz, Pu, Yunchen, Xie, Xinfeng, He, Xingfeng, Xu, Fangzhou, Cui, Andrew, Viswanathan, Vidhoon, Dong, Yan, Xiong, Liang, Yang, Lin, Wang, Liang, Yang, Jiyan, Sun, Chonglin
Embedding Based Retrieval (EBR) is a crucial component of the retrieval stage in (Ads) Recommendation System that utilizes Two Tower or Siamese Networks to learn embeddings for both users and items (ads). It then employs an Approximate Nearest Neighb
Externí odkaz:
http://arxiv.org/abs/2408.06653
Autor:
Wen, Wei, Liu, Kuang-Hung, Fedorov, Igor, Zhang, Xin, Yin, Hang, Chu, Weiwei, Hassani, Kaveh, Sun, Mengying, Liu, Jiang, Wang, Xu, Jiang, Lin, Chen, Yuxin, Zhang, Buyun, Liu, Xi, Cheng, Dehua, Chen, Zhengxing, Zhao, Guang, Han, Fangqiu, Yang, Jiyan, Hao, Yuchen, Xiong, Liang, Chen, Wen-Yen
Neural Architecture Search (NAS) has demonstrated its efficacy in computer vision and potential for ranking systems. However, prior work focused on academic problems, which are evaluated at small scale under well-controlled fixed baselines. In indust
Externí odkaz:
http://arxiv.org/abs/2311.08430
Autor:
Yajie Dai, Claudia Voigt, Enrico Storti, Jana Hubálková, Patrick Gehre, Xiong Liang, Wen Yan, Yawei Li, Christos G. Aneziris
Publikováno v:
Journal of Materials Research and Technology, Vol 32, Iss , Pp 3402-3422 (2024)
Open-cell ceramic foams are widely used as filters for the purification of molten metals due to their high permeability and high efficiency for capturing non-metallic inclusions. With the consideration of manufacture and filtration behaviour, most fi
Externí odkaz:
https://doaj.org/article/b14de68f97f24218b80b53b91c91f1fa
Autor:
Zhang, Tunhou, Cheng, Dehua, He, Yuchen, Chen, Zhengxing, Dai, Xiaoliang, Xiong, Liang, Yan, Feng, Li, Hai, Chen, Yiran, Wen, Wei
Publikováno v:
Proceedings of the ACM Web Conference 2023 (WWW'23)
The rise of deep neural networks offers new opportunities in optimizing recommender systems. However, optimizing recommender systems using deep neural networks requires delicate architecture fabrication. We propose NASRec, a paradigm that trains a si
Externí odkaz:
http://arxiv.org/abs/2207.07187
Publikováno v:
In Journal of Materials Research and Technology November-December 2024 33:4763-4771
Autor:
Liu, Yufei, Xiong, Liang, Gao, Bingyang, Shi, Qingyun, Wang, Ying, Wang, Chunli, Wang, Limin, Cheng, Yong
Publikováno v:
In International Journal of Hydrogen Energy 11 October 2024 86:835-843
Publikováno v:
In Geoenergy Science and Engineering October 2024 241