Zobrazeno 1 - 10
of 580
pro vyhledávání: '"Wu Bang"'
The prosperity of Decentralized Finance (DeFi) unveils underlying risks, with reported losses surpassing 3.2 billion USD between 2018 and 2022 due to vulnerabilities in Decentralized Applications (DApps). One significant threat is the Price Manipulat
Externí odkaz:
http://arxiv.org/abs/2406.11157
Graph unlearning has emerged as an essential tool for safeguarding user privacy and mitigating the negative impacts of undesirable data. Meanwhile, the advent of dynamic graph neural networks (DGNNs) marks a significant advancement due to their super
Externí odkaz:
http://arxiv.org/abs/2405.14407
Autor:
Wang, Xu-Jie, Huang, Guoqi, Li, Ming-Yang, Wang, Yuan-Zhuo, Liu, Li, Wu, Bang, Liu, Hanqing, Ni, Haiqiao, Niu, Zhichuan, Ji, Weijie, Jiao, Rongzhen, Yin, Hua-Lei, Yuan, Zhiliang
Resonance fluorescence (RF) of a two-level emitter displays persistently anti-bunching irrespective of the excitation intensity, but inherits the driving laser's linewidth under weak excitation. These properties are commonly explained disjoinedly as
Externí odkaz:
http://arxiv.org/abs/2312.13743
The deployment of Graph Neural Networks (GNNs) within Machine Learning as a Service (MLaaS) has opened up new attack surfaces and an escalation in security concerns regarding model-centric attacks. These attacks can directly manipulate the GNN model
Externí odkaz:
http://arxiv.org/abs/2312.07870
The emergence of Graph Neural Networks (GNNs) in graph data analysis and their deployment on Machine Learning as a Service platforms have raised critical concerns about data misuse during model training. This situation is further exacerbated due to t
Externí odkaz:
http://arxiv.org/abs/2312.07861
Publikováno v:
E3S Web of Conferences, Vol 233, p 03057 (2021)
Sensor failures can lead to an imbalance in heating, ventilation and air conditioning (HVAC) control systems and increase energy consumption. The partial least squares algorithm is a multivariate statistical method, compared with the principal compon
Externí odkaz:
https://doaj.org/article/b4c60b0e69cb45e9802e0eb10718e71b
Autor:
Wu, Bang, Wang, Xu-Jie, Liu, Li, Huang, Guoqi, Wang, Wenyan, Liu, Hanqing, Ni, Haiqiao, Niu, Zhichuan, Yuan, Zhiliang
Publikováno v:
Optica 10, 1118 (2023)
Resonant excitation is an essential tool in the development of semiconductor quantum dots (QDs) for quantum information processing. One central challenge is to enable a transparent access to the QD signal without post-selection information loss. A vi
Externí odkaz:
http://arxiv.org/abs/2305.12719
Publikováno v:
Yankuang ceshi, Vol 34, Iss 1, Pp 12-18 (2015)
For coarse gold-containing ore, the existence of the coarse grained gold makes it challenging to collect, process and analyze ore samples, so the issue of how to obtain representative samples with great uniformity for chemical analysis, and provide a
Externí odkaz:
https://doaj.org/article/801c618766504a2d90af3712473a3df5
The function call graph (FCG) based Android malware detection methods have recently attracted increasing attention due to their promising performance. However, these methods are susceptible to adversarial examples (AEs). In this paper, we design a no
Externí odkaz:
http://arxiv.org/abs/2303.08509
Graph neural networks (GNNs) have emerged as a series of competent graph learning methods for diverse real-world scenarios, ranging from daily applications like recommendation systems and question answering to cutting-edge technologies such as drug d
Externí odkaz:
http://arxiv.org/abs/2205.07424