Zobrazeno 1 - 10
of 650
pro vyhledávání: '"Qiu, Meikang"'
Model Inversion (MI) attacks aim to reconstruct privacy-sensitive training data from released models by utilizing output information, raising extensive concerns about the security of Deep Neural Networks (DNNs). Recent advances in generative adversar
Externí odkaz:
http://arxiv.org/abs/2407.13863
Self-consistent Deep Geometric Learning for Heterogeneous Multi-source Spatial Point Data Prediction
Multi-source spatial point data prediction is crucial in fields like environmental monitoring and natural resource management, where integrating data from various sensors is the key to achieving a holistic environmental understanding. Existing models
Externí odkaz:
http://arxiv.org/abs/2407.00748
Dataset distillation is an emerging dataset reduction method, which condenses large-scale datasets while maintaining task accuracy. Current methods have integrated parameterization techniques to boost synthetic dataset performance by shifting the opt
Externí odkaz:
http://arxiv.org/abs/2406.05704
Autor:
Liu, Xiao-Yang, Zhu, Rongyi, Zha, Daochen, Gao, Jiechao, Zhong, Shan, White, Matt, Qiu, Meikang
The surge in interest and application of large language models (LLMs) has sparked a drive to fine-tune these models to suit specific applications, such as finance and medical science. However, concerns regarding data privacy have emerged, especially
Externí odkaz:
http://arxiv.org/abs/2312.17493
Visual explanation (attention)-guided learning uses not only labels but also explanations to guide model reasoning process. While visual attention-guided learning has shown promising results, it requires a large number of explanation annotations that
Externí odkaz:
http://arxiv.org/abs/2310.08420
Autor:
Wang, Jiapu, Wang, Boyue, Qiu, Meikang, Pan, Shirui, Xiong, Bo, Liu, Heng, Luo, Linhao, Liu, Tengfei, Hu, Yongli, Yin, Baocai, Gao, Wen
Temporal characteristics are prominently evident in a substantial volume of knowledge, which underscores the pivotal role of Temporal Knowledge Graphs (TKGs) in both academia and industry. However, TKGs often suffer from incompleteness for three main
Externí odkaz:
http://arxiv.org/abs/2308.02457