5 citations · 8 across the 8 of their papers we have counts for
13 papers
Not All Instances Contribute Equally: Instance-adaptive Class Representation Learning for Few-Shot Visual Recognition
Mengya Han, Yibing Zhan, Yong Luo +4
Few-shot visual recognition refers to recognize novel visual concepts from a few labeled instances. Many few-shot visual recognition methods adopt the metric-based meta-learning pa…
CDFKD-MFS: Collaborative Data-free Knowledge Distillation via Multi-level Feature Sharing
Zhiwei Hao, Yong Luo, Zhi Wang +2
Recently, the compression and deployment of powerful deep neural networks (DNNs) on resource-limited edge devices to provide intelligent services have become attractive tasks. Alth…
Intelligent Resource Allocations for IRS-Assisted OFDM Communications: A Hybrid MDQN-DDPG Approach
Wei Wu, Fengchun Yang, Fuhui Zhou +3
In this paper, we study the resource allocation problem for an intelligent reflecting surface (IRS)-assisted OFDM system. The system sum rate maximization framework is formulated b…
Energy Efficiency and Delay Tradeoff in an MEC-Enabled Mobile IoT Network
Han Hu, Weiwei Song, Qun Wang +2
Mobile Edge Computing (MEC) has recently emerged as a promising technology in the 5G era. It is deemed an effective paradigm to support computation-intensive and delay critical app…
Joint Task Offloading and Resource Allocation for IoT Edge Computing with Sequential Task Dependency
Xuming An, Rongfei Fan, Han Hu +3
Incorporating mobile edge computing (MEC) in the Internet of Things (IoT) enables resource-limited IoT devices to offload their computation tasks to a nearby edge server. In this p…
Energy-Efficient Design for IRS-Assisted MEC Networks with NOMA
Qun Wang, Fuhui Zhou, Han Hu +1
Energy-efficient design is of crucial importance in wireless internet of things (IoT) networks. In order to serve massive users while achieving an energy-efficient operation, an in…