1 code implementation • 8 Apr 2021 • Juncheng Lv, Zhao Kang, Xiao Lu, Zenglin Xu
To tackle these problems, we use pairwise similarity to weigh the reconstruction loss to capture local structure information, while a similarity is learned by the self-expression layer.
1 code implementation • CVPR 2022 • Xiao Lu, Yihong Cao, Sheng Liu, Chengjiang Long, Zipei Chen, Xuanyu Zhou, Yimin Yang, Chunxia Xiao
Our proposed approach is extensively validated on the ViSha dataset and a self-annotated dataset.
2 code implementations • 2 Jun 2023 • Yihong Cao, HUI ZHANG, Xiao Lu, Zheng Xiao, Kailun Yang, Yaonan Wang
It utilizes a well-trained source model and unlabeled target data to achieve adaptation in the target domain.
no code implementations • 20 Jun 2018 • Zhao Kang, Xiao Lu, Jin-Feng Yi, Zenglin Xu
There are two possible reasons for the failure: (i) most existing MKL methods assume that the optimal kernel is a linear combination of base kernels, which may not hold true; and (ii) some kernel weights are inappropriately assigned due to noises and carelessly designed algorithms.
no code implementations • 20 Feb 2019 • Yishen Wang, Xiao Lu, Yiran Xu, Di Shi, Zhehan Yi, Jiajun Duan, Zhiwei Wang
Traditional load analysis is facing challenges with the new electricity usage patterns due to demand response as well as increasing deployment of distributed generations, including photovoltaics (PV), electric vehicles (EV), and energy storage systems (ESS).
no code implementations • 26 Mar 2019 • Qicheng Chang, Yishen Wang, Xiao Lu, Di Shi, Haifeng Li, Jiajun Duan, Zhiwei Wang
In the first stage, all related features are utilized to train a point forecast model and also obtain the feature importance.
no code implementations • 26 Mar 2019 • Yayu Peng, Yishen Wang, Xiao Lu, Haifeng Li, Di Shi, Zhiwei Wang, Jie Li
Short-term load forecasting (STLF) is essential for the reliable and economic operation of power systems.
no code implementations • 3 Dec 2019 • Zhao Kang, Xiao Lu, Yiwei Lu, Chong Peng, Zenglin Xu
Leveraging on the underlying low-dimensional structure of data, low-rank and sparse modeling approaches have achieved great success in a wide range of applications.
no code implementations • 8 Dec 2019 • Guangxia Lia, Yulong Shena, Peilin Zhaob, Xiao Lu, Jia Liu, Yangyang Liu, Steven C. H. Hoi
Similar to other information systems, a significant threat to industrial control systems is the attack from cyberspace---the offensive maneuvers launched by "anonymous" in the digital world that target computer-based assets with the goal of compromising a system's functions or probing for information.
no code implementations • 11 Jul 2020 • Zhao Kang, Xiao Lu, Jian Liang, Kun Bai, Zenglin Xu
In this work, we propose a new representation learning method that explicitly models and leverages sample relations, which in turn is used as supervision to guide the representation learning.
no code implementations • 26 Jul 2020 • Nguyen Cong Luong, Xiao Lu, Dinh Thai Hoang, Dusit Niyato, Dong In Kim
First, we give fundamental concepts of JRC, important performance metrics used in JRC systems, and applications of the JRC systems.
no code implementations • 2 Feb 2021 • Xiao Lu, Dusit Niyato, Hai Jiang, Ekram Hossain, Ping Wang
With different mode selection protocols, we characterize the success probability and ergodic capacity of a dual-hop relaying system with the hybrid relay in the field of randomly located ambient transmitters.
Information Theory Networking and Internet Architecture Information Theory
no code implementations • 18 Nov 2022 • Xiang Wang, Yimin Yang, Qixiang Pang, Xiao Lu, Yu Liu, Shan Du
In this paper, we propose a novel face super-resolution method, namely Semantic Encoder guided Generative Adversarial Face Ultra-Resolution Network (SEGA-FURN) to ultra-resolve an unaligned tiny LR face image to its HR counterpart with multiple ultra-upscaling factors (e. g., 4x and 8x).