Zobrazeno 1 - 10
of 14 559
pro vyhledávání: '"WU, Peng"'
New insights from the Dark Energy Spectroscopic Instrument (DESI) 2024 baryon acoustic oscillations (BAO) data, in conjunction with cosmic microwave background (CMB) and Type Ia supernova (SN) data, suggest that dark energy may not be a cosmological
Externí odkaz:
http://arxiv.org/abs/2411.08639
Autor:
Wu, Peng-Ju, Zhang, Xin
The cosmic curvature $\Omega_{K}$ is an important parameter related to the inflationary cosmology and the ultimate fate of the universe. In this work, we adopt the non-CMB observations to constrain $\Omega_{K}$ in the $\Lambda$CDM model and its exten
Externí odkaz:
http://arxiv.org/abs/2411.06356
One of the main challenges of federated learning (FL) is handling non-independent and identically distributed (non-IID) client data, which may occur in practice due to unbalanced datasets and use of different data sources across clients. Knowledge sh
Externí odkaz:
http://arxiv.org/abs/2410.15473
Publikováno v:
Journal of Zhengzhou University(Natural Science Edition),2022,54 (05), 43-48
A symmetric nonnegative matrix factorization algorithm based on self-paced learning was proposed to improve the clustering performance of the model. It could make the model better distinguish normal samples from abnormal samples in an error-driven wa
Externí odkaz:
http://arxiv.org/abs/2410.15306
Unsupervised feature selection algorithm framework based on neighborhood interval disturbance fusion
Publikováno v:
Journal of Nanjing University of Science and Technology, 2021, 45(04), 420-428
Feature selection technology is a key technology of data dimensionality reduction. Becauseof the lack of label information of collected data samples, unsupervised feature selection has attracted more attention. The universality and stability of many
Externí odkaz:
http://arxiv.org/abs/2410.15294
In recent years, the study of adversarial robustness in object detection systems, particularly those based on deep neural networks (DNNs), has become a pivotal area of research. Traditional physical attacks targeting object detectors, such as adversa
Externí odkaz:
http://arxiv.org/abs/2410.10091
Recommending items solely catering to users' historical interests narrows users' horizons. Recent works have considered steering target users beyond their historical interests by directly adjusting items exposed to them. However, the recommended item
Externí odkaz:
http://arxiv.org/abs/2409.08934
Video anomaly detection (VAD) aims to discover behaviors or events deviating from the normality in videos. As a long-standing task in the field of computer vision, VAD has witnessed much good progress. In the era of deep learning, with the explosion
Externí odkaz:
http://arxiv.org/abs/2409.05383
Autor:
Wen, Runkai, Chai, Yukun, Wang, Lingxin, Du, Ruochen, Long, Xingtian, Liu, Zhiyang, Wu, Peng, Wang, Yiduo
A class of quasi-distribution evaluation criteria based on piecewise Bezier curves is proposed to address the issue of the inability to objectively evaluate finite element models. During the optimization design of mechanical parts, finite element mod
Externí odkaz:
http://arxiv.org/abs/2409.03987
We innovate a systematic investigation of the Weak Cosmic Censorship Conjecture (WCCC) using gedanken experiments involving black hole perturbations by test particles. We classify various WCCC violation scenarios proposed in recent decades, including
Externí odkaz:
http://arxiv.org/abs/2408.09444