Zobrazeno 1 - 10
of 18 938
pro vyhledávání: '"Zhou Yong"'
Space-ground integrated networks hold great promise for providing global connectivity, particularly in remote areas where large amounts of valuable data are generated by Internet of Things (IoT) devices, but lacking terrestrial communication infrastr
Externí odkaz:
http://arxiv.org/abs/2408.14116
Considered here are robust subgroup-classifier learning and testing in change-plane regressions with heavy-tailed errors, which can identify subgroups as a basis for making optimal recommendations for individualized treatment. A new subgroup classifi
Externí odkaz:
http://arxiv.org/abs/2408.14036
The forthcoming generation of wireless technology, 6G, promises a revolutionary leap beyond traditional data-centric services. It aims to usher in an era of ubiquitous intelligent services, where everything is interconnected and intelligent. This vis
Externí odkaz:
http://arxiv.org/abs/2408.08074
Considered here is a hypothesis test for the coefficients in the change-plane regression models to detect the existence of a change plane. The test that is considered is from the class of test problems in which some parameters are not identifiable un
Externí odkaz:
http://arxiv.org/abs/2408.00602
With the development of deep learning, many different network architectures have been explored in speaker verification. However, most network architectures rely on a single deep learning architecture, and hybrid networks combining different architect
Externí odkaz:
http://arxiv.org/abs/2407.03135
Pre-trained foundation models (FMs), with extensive number of neurons, are key to advancing next-generation intelligence services, where personalizing these models requires massive amount of task-specific data and computational resources. The prevale
Externí odkaz:
http://arxiv.org/abs/2407.02924
Deep learning models are widely used for speaker recognition and spoofing speech detection. We propose the GMM-ResNet2 for synthesis speech detection. Compared with the previous GMM-ResNet model, GMM-ResNet2 has four improvements. Firstly, the differ
Externí odkaz:
http://arxiv.org/abs/2407.02170
The proliferation of low-earth-orbit (LEO) satellite networks leads to the generation of vast volumes of remote sensing data which is traditionally transferred to the ground server for centralized processing, raising privacy and bandwidth concerns. F
Externí odkaz:
http://arxiv.org/abs/2404.01875
In multi-label classification, each training instance is associated with multiple class labels simultaneously. Unfortunately, collecting the fully precise class labels for each training instance is time- and labor-consuming for real-world application
Externí odkaz:
http://arxiv.org/abs/2403.16482
Long-tailed data is prevalent in real-world classification tasks and heavily relies on supervised information, which makes the annotation process exceptionally labor-intensive and time-consuming. Unfortunately, despite being a common approach to miti
Externí odkaz:
http://arxiv.org/abs/2403.16469