Zobrazeno 1 - 10
of 2 773
pro vyhledávání: '"LIU, XIAOLEI"'
Autor:
Ning, Xuying, Xu, Wujiang, Liu, Xiaolei, Ha, Mingming, Ma, Qiongxu, Li, Youru, Chen, Linxun, Zhang, Yongfeng
Cross-Domain Sequential Recommendation (CDSR) methods aim to address the data sparsity and cold-start problems present in Single-Domain Sequential Recommendation (SDSR). Existing CDSR methods typically rely on overlapping users, designing complex cro
Externí odkaz:
http://arxiv.org/abs/2405.20710
Autor:
Chen, Renqi, Han, Wenwei, Zhang, Haohao, Su, Haoyang, Wang, Zhefan, Liu, Xiaolei, Jiang, Hao, Ouyang, Wanli, Dong, Nanqing
Genomic selection (GS), as a critical crop breeding strategy, plays a key role in enhancing food production and addressing the global hunger crisis. The predominant approaches in GS currently revolve around employing statistical methods for predictio
Externí odkaz:
http://arxiv.org/abs/2405.09585
SUB-PLAY: Adversarial Policies against Partially Observed Multi-Agent Reinforcement Learning Systems
Autor:
Ma, Oubo, Pu, Yuwen, Du, Linkang, Dai, Yang, Wang, Ruo, Liu, Xiaolei, Wu, Yingcai, Ji, Shouling
Recent advancements in multi-agent reinforcement learning (MARL) have opened up vast application prospects, such as swarm control of drones, collaborative manipulation by robotic arms, and multi-target encirclement. However, potential security threat
Externí odkaz:
http://arxiv.org/abs/2402.03741
Publikováno v:
Sichuan jingshen weisheng, Vol 37, Iss 5, Pp 475-481 (2024)
BackgroundClozapine belongs to atypical antipsychotic drugs that has shown significant efficacy in treating schizophrenia. However， clozapine can induce arrhythmias in patients. Currently， there is a lack of systematic research on the types and i
Externí odkaz:
https://doaj.org/article/13f3bf85781f4a029f47cdef255feed4
Model inversion attacks (MIAs) aim to recover private data from inaccessible training sets of deep learning models, posing a privacy threat. MIAs primarily focus on the white-box scenario where attackers have full access to the model's structure and
Externí odkaz:
http://arxiv.org/abs/2307.08424
Deep learning models are vulnerable to backdoor attacks, where attackers inject malicious behavior through data poisoning and later exploit triggers to manipulate deployed models. To improve the stealth and effectiveness of backdoors, prior studies h
Externí odkaz:
http://arxiv.org/abs/2304.10985
Autor:
Xu, Wujiang, Li, Shaoshuai, Ha, Mingming, Guo, Xiaobo, Ma, Qiongxu, Liu, Xiaolei, Chen, Linxun, Zhu, Zhenfeng
Publikováno v:
The IEEE International Conference on Data Engineering 2023
Multi-Target Cross Domain Recommendation(CDR) has attracted a surge of interest recently, which intends to improve the recommendation performance in multiple domains (or systems) simultaneously. Most existing multi-target CDR frameworks primarily rel
Externí odkaz:
http://arxiv.org/abs/2302.05919
Autor:
Xi, Xiaoting1 (AUTHOR), Liu, Xiaolei2 (AUTHOR), Chen, Qianbo1 (AUTHOR), Ma, Jia1 (AUTHOR), Wang, Xuewei1 (AUTHOR), Gui, Yufei1 (AUTHOR), Zhang, Yuxin1 (AUTHOR), Li, Yan1 (AUTHOR) li_yan_km@163.com
Publikováno v:
PLoS ONE. 12/17/2024, Vol. 19 Issue 12, p1-23. 23p.
Autor:
Sun, Chengfa1 (AUTHOR) 201920518@mail.sdu.edu.cn, Liu, Xiaolei2 (AUTHOR) lixinpu2005@163.com, Liu, Changchun1 (AUTHOR) changchunliu@sdu.edu.cn, Wang, Xinpei1 (AUTHOR) changchunliu@sdu.edu.cn, Liu, Yuanyuan1 (AUTHOR), Zhao, Shilong1 (AUTHOR), Zhang, Ming3 (AUTHOR) zhangmingzw@163.com
Publikováno v:
Bioengineering (Basel). Nov2024, Vol. 11 Issue 11, p1093. 20p.
Autor:
Liu, Xiaolei1 (AUTHOR) liuxiaolei0302@126.com, Yang, Peijun1 (AUTHOR), Liu, Liguo1 (AUTHOR), Si, Shuang1 (AUTHOR), Zhou, Ruiquan1 (AUTHOR), Liu, Tiantong1 (AUTHOR), Tan, Haidong1 (AUTHOR) hpblt_cjfh@126.com
Publikováno v:
BMC Cancer. 10/16/2024, Vol. 24 Issue 1, p1-10. 10p.