no code implementations • 8 Jan 2024 • Yuhan Tang, Zhiyuan Wu, Bo Gao, Tian Wen, Yuwei Wang, Sheng Sun
Federated Distillation (FD) is a novel and promising distributed machine learning paradigm, where knowledge distillation is leveraged to facilitate a more efficient and flexible cross-device knowledge transfer in federated learning.
no code implementations • 25 Jan 2023 • Xuan Jiang, Yuhan Tang, Zhiyi Tang, Junzhe Cao, Vishwanath Bulusu, Xin Peng, Cristian Poliziani, Raja Sengupta
Urban air mobility (UAM) has the potential to revolutionize transportation in metropolitan areas, providing a new mode of transportation that could alleviate congestion and improve accessibility.
no code implementations • 27 Apr 2020 • Ruizhen Hu, Zeyu Huang, Yuhan Tang, Oliver van Kaick, Hao Zhang, Hui Huang
The core component of our learning framework is a deep neural network, Graph2Plan, which converts a layout graph, along with a building boundary, into a floorplan that fulfills both the layout and boundary constraints.