Zobrazeno 1 - 10
of 14 687
pro vyhledávání: '"ZHOU, Peng"'
The ability to wield tools was once considered exclusive to human intelligence, but it's now known that many other animals, like crows, possess this capability. Yet, robotic systems still fall short of matching biological dexterity. In this paper, we
Externí odkaz:
http://arxiv.org/abs/2412.06931
Distilling 3D representations from pretrained 2D diffusion models is essential for 3D creative applications across gaming, film, and interior design. Current SDS-based methods are hindered by inefficient information distillation from diffusion models
Externí odkaz:
http://arxiv.org/abs/2412.05929
Under stringent privacy constraints, whether federated recommendation systems can achieve group fairness remains an inadequately explored question. Taking gender fairness as a representative issue, we identify three phenomena in federated recommendat
Externí odkaz:
http://arxiv.org/abs/2411.19678
Publikováno v:
Journal of Jilin University(Science Edition),2024,62(03),655-664
Aiming at the problem that existing methods could not fully capture the intrinsic structure of data without considering the higher-order neighborhood information of the data, we proposed an unsupervised feature selection algorithm based on graph filt
Externí odkaz:
http://arxiv.org/abs/2411.00270
Publikováno v:
Journal of Computer Applications, 2023, 43(9),2665-2672
Most of the research on clustering ensemble focuses on designing practical consistency learning algorithms.To solve the problems that the quality of base clusters varies and the low-quality base clusters have an impact on the performance of the clust
Externí odkaz:
http://arxiv.org/abs/2411.00268
Publikováno v:
Computer Science, 2023, 50(02), 138-145
Multiple kernel learning (MKL) aims to find an optimal, consistent kernel function. In the hierarchical multiple kernel clustering (HMKC) algorithm, sample features are extracted layer by layer from a high-dimensional space to maximize the retention
Externí odkaz:
http://arxiv.org/abs/2410.20391
Publikováno v:
Computer Science, 2023,50(07),72-81
High-dimensional data is commonly encountered in numerous data analysis tasks. Feature selection techniques aim to identify the most representative features from the original high-dimensional data. Due to the absence of class label information, it is
Externí odkaz:
http://arxiv.org/abs/2410.20388
Observation of quantum information collapse-and-revival in a strongly-interacting Rydberg atom array
Autor:
Xiang, De-Sheng, Zhang, Yao-Wen, Liu, Hao-Xiang, Zhou, Peng, Yuan, Dong, Zhang, Kuan, Zhang, Shun-Yao, Xu, Biao, Liu, Lu, Li, Yitong, Li, Lin
Interactions of isolated quantum many-body systems typically scramble local information into the entire system and make it unrecoverable. Ergodicity-breaking systems possess the potential to exhibit fundamentally different information scrambling dyna
Externí odkaz:
http://arxiv.org/abs/2410.15455
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
Publikováno v:
Computer Science, 2021,48(08),47-52
Multiple kernel methods less consider the intrinsic manifold structure of multiple kernel data and estimate the consensus kernel matrix with quadratic number of variables, which makes it vulnerable to the noise and outliers within multiple candidate
Externí odkaz:
http://arxiv.org/abs/2410.15304