46 citations · 53 across the 6 of their papers we have counts for
6 papers
Efficient Asynchronous Federated Learning with Sparsification and Quantization
Juncheng Jia, Ji Liu, Chendi Zhou +3
While data is distributed in multiple edge devices, Federated Learning (FL) is attracting more and more attention to collaboratively train a machine learning model without transfer…
Spectral Enhanced Rectangle Transformer for Hyperspectral Image Denoising
Miaoyu Li, Ji Liu, Ying Fu +2
Denoising is a crucial step for hyperspectral image (HSI) applications. Though witnessing the great power of deep learning, existing HSI denoising methods suffer from limitations i…
LG-BPN: Local and Global Blind-Patch Network for Self-Supervised Real-World Denoising
Zichun Wang, Ying Fu, Ji Liu +1
Despite the significant results on synthetic noise under simplified assumptions, most self-supervised denoising methods fail under real noise due to the strong spatial noise correl…
HPS-Det: Dynamic Sample Assignment with Hyper-Parameter Search for Object Detection
Ji Liu, Dong Li, Zekun Li +4
Sample assignment plays a prominent part in modern object detection approaches. However, most existing methods rely on manual design to assign positive / negative samples, which do…
Multi-Entanglement Routing Design over Quantum Networks
Yiming Zeng, Jiarui Zhang, Ji Liu +2
Quantum networks are considered as a promising future platform for quantum information exchange and quantum applications, which have capabilities far beyond the traditional communi…
Proximal Reinforcement Learning: A New Theory of Sequential Decision Making in Primal-Dual Spaces
Sridhar Mahadevan, Bo Liu, Philip Thomas +5
In this paper, we set forth a new vision of reinforcement learning developed by us over the past few years, one that yields mathematically rigorous solutions to longstanding import…