1 citations · 1 across the 5 of their papers we have counts for
5 papers
Low-Complexity Inference in Continual Learning via Compressed Knowledge Transfer
Zhenrong Liu, Janne M. J. Huttunen, Mikko Honkala
Continual learning (CL) aims to train models that can learn a sequence of tasks without forgetting previously acquired knowledge. A core challenge in CL is balancing stability -- p…
RIS-Aided Cooperative Mobile Edge Computing: Computation Efficiency Maximization via Joint Uplink and Downlink Resource Allocation
Zhenrong Liu, Zongze Li, Yi Gong +1
In mobile edge computing (MEC) systems, the wireless channel condition is a critical factor affecting both the communication power consumption and computation rate of the offloadin…
Learning a Low-Rank Feature Representation: Achieving Better Trade-Off between Stability and Plasticity in Continual Learning
Zhenrong Liu, Yang Li, Yi Gong +1
In continual learning, networks confront a trade-off between stability and plasticity when trained on a sequence of tasks. To bolster plasticity without sacrificing stability, we p…
STAR-RIS-Aided Mobile Edge Computing: Computation Rate Maximization with Binary Amplitude Coefficients
Zhenrong Liu, Zongze Li, Miaowen Wen +2
In this paper, simultaneously transmitting and reflecting (STAR) reconfigurable intelligent surface (RIS) is investigated in the multi-user mobile edge computing (MEC) system to im…
Simultaneously Transmitting and Reflecting RIS-Aided Mobile Edge Computing: Computation Rate Maximization
Zhenrong Liu, Zongze Li, Miaowen Wen +2
In this paper, the novel simultaneously transmitting and reflecting (STAR) reconfigurable intelligent surface (RIS), which enables full-space coverage on users located on both side…