1.4k citations · 2.6k across the 41 of their papers we have counts for
13 papers · 1 filter
Open World DETR: Transformer based Open World Object Detection
Na Dong, Yongqiang Zhang, Mingli Ding +1
Open world object detection aims at detecting objects that are absent in the object classes of the training data as unknown objects without explicit supervision. Furthermore, the e…
Decentralized Federated Reinforcement Learning for User-Centric Dynamic TFDD Control
Ziyan Yin, Zhe Wang, Jun Li +3
The explosive growth of dynamic and heterogeneous data traffic brings great challenges for 5G and beyond mobile networks. To enhance the network capacity and reliability, we propos…
Low-latency Federated Learning with DNN Partition in Distributed Industrial IoT Networks
Xiumei Deng, Jun Li, Chuan Ma +4
Federated Learning (FL) empowers Industrial Internet of Things (IIoT) with distributed intelligence of industrial automation thanks to its capability of distributed machine learnin…
GLM-130B: An Open Bilingual Pre-trained Model
Aohan Zeng, Xiao Liu, Zhengxiao Du +15
We introduce GLM-130B, a bilingual (English and Chinese) pre-trained language model with 130 billion parameters. It is an attempt to open-source a 100B-scale model at least as good…
Intelligent Blockchain-based Edge Computing via Deep Reinforcement Learning: Solutions and Challenges
Dinh C. Nguyen, Van-Dinh Nguyen, Ming Ding +5
The convergence of mobile edge computing (MEC) and blockchain is transforming the current computing services in wireless Internet-of-Things networks, by enabling task offloading wi…
Rethinking the Setting of Semi-supervised Learning on Graphs
Ziang Li, Ming Ding, Weikai Li +4
We argue that the present setting of semisupervised learning on graphs may result in unfair comparisons, due to its potential risk of over-tuning hyper-parameters for models. In th…