no code implementations • 22 May 2024 • Handong Bai, Peng Li, Hongwei Zhang
Restricting bus voltage deviation is crucial for normal operation of multi-bus DC microgrids, yet it has received insufficient attention due to the conflict between two main control objectives in DC microgrids, i. e., voltage regulation and current sharing.
no code implementations • 12 Mar 2024 • Hongwei Zhang, Xiaoyin Xu, Dongsheng An, Xianfeng GU, Min Zhang
Backdoor attacks become a significant security concern for deep neural networks in recent years.
no code implementations • 8 Dec 2023 • Shengzhong Zhang, Wenjie Yang, Yimin Zhang, Hongwei Zhang, Divin Yan, Zengfeng Huang
In this work, we discover a phenomenon of community bias amplification in graph representation learning, which refers to the exacerbation of performance bias between different classes by graph representation learning.
1 code implementation • 8 Dec 2023 • Shengzhong Zhang, Wenjie Yang, Xinyuan Cao, Hongwei Zhang, Zengfeng Huang
This allows the encoder not to perform any message passing during the training stage, and significantly reduces the number of sample pairs in the contrastive loss.
1 code implementation • 11 Jun 2022 • Wenjian Luo, Hongwei Zhang, Linghao Kong, Zhijian Chen, Ke Tang
The security issues in DNNs, such as adversarial examples, have attracted much attention.
1 code implementation • 30 Apr 2022 • Hongwei Zhang, Shuo Shao, Meixia Tao, Xiaoyan Bi, Khaled B. Letaief
In practice, the semantic information is defined by the pragmatic task of the receiver and cannot be known to the transmitter.
no code implementations • 29 Dec 2021 • Shimin Wang, Xiangyu Meng, Hongwei Zhang, Frank L. Lewis
This paper proposes a learning-based fully distributed observer for a class of nonlinear leader systems, which can simultaneously learn the leader's dynamics and states.
no code implementations • 9 Oct 2021 • Qishen Ha, Bo Liu, Hongwei Zhang
We present our solutions to the Google Landmark Challenges 2021, for both the retrieval and the recognition tracks.
no code implementations • 4 Jul 2021 • Hongwei Zhang, Weidong Zou, Hongbo Zhao, Qi Ming, Tijin Yan, Yuanqing Xia, Weipeng Cao
Inspired by this, we propose AdaL, with a transformation on the original gradient.
1 code implementation • 18 Jun 2021 • Tijin Yan, Hongwei Zhang, Tong Zhou, Yufeng Zhan, Yuanqing Xia
However, many existing works can not be widely used because of the constraints of functional form of generative models or the sensitivity to hyperparameters.
no code implementations • 12 Apr 2021 • Xianjie Gao, Xueguan Song, Maolin Shi, Chao Zhang, Hongwei Zhang
In this paper, based on in-situ TBM operational data, we use the machine-learning (ML) methods to build the real-time forecast models for TBM load parameters, which can instantaneously provide the future values of the TBM load parameters as long as the current data are collected.
2 code implementations • 8 Dec 2020 • Qi Ming, Zhiqiang Zhou, Lingjuan Miao, Hongwei Zhang, Linhao Li
With the newly introduced DAL, we achieve superior detection performance for arbitrary-oriented objects with only a few horizontal preset anchors.
Ranked #1 on Multi-Oriented Scene Text Detection on ICDAR2015 (using extra training data)
no code implementations • 24 Sep 2020 • Hongwei Zhang, Tijin Yan, Zenjun Xie, Yuanqing Xia, Yuan Zhang
Based on our theoretical and empirical analysis, we establish a universal theoretical framework of GCN from an optimization perspective and derive a novel convolutional kernel named GCN+ which has lower parameter amount while relieving the over-smoothing inherently.
no code implementations • 1 Sep 2020 • Tijin Yan, Hongwei Zhang, Zirui Li, Yuanqing Xia
In addition, to alleviate KL-vanishing problem in SGRNN, a simple and interpretable structure is proposed based on the lower bound of KL-divergence.
no code implementations • 25 Jun 2020 • Lucas J. Liu, Hongwei Zhang, Jianzhong Di, Jin Chen
We propose a novel Ensemble-Learning for Missing Value (ELMV) framework, which introduces an effective approach to construct multiple subsets of the original EHR data with a much lower missing rate, as well as mobilizing a dedicated support set for the ensemble learning in the purpose of reducing the bias caused by substantial missing values.
no code implementations • 24 Mar 2020 • Shimin Wang, Hongwei Zhang, Zhiyong Chen
Distributed adaptive observers are designed for all follower nodes, simultaneously estimate the state and parameters of the leader node.