484 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Shandong Academy of SciencesCN58 papers
- Shandong UniversityCN15 papers
- Shandong Normal UniversityCN13 papers
- National University of SingaporeSG9 papers
- University of MacauMO8 papers
- Changchun Institute of TechnologyCN7 papers
- Institute of Oceanographic InstrumentationCN7 papers
- Deakin UniversityAU6 papers
- Shandong University of Finance and EconomicsCN6 papers
- Chinese Academy of SciencesCN5 papers
- Monash UniversityAU5 papers
- Northeast Electric Power UniversityCN5 papers
11 papers · 1 filter
The Eminence in Shadow: Exploiting Feature Boundary Ambiguity for Robust Backdoor Attacks
Zhou Feng, Jiahao Chen, Chunyi Zhou +5
Deep neural networks (DNNs) underpin critical applications yet remain vulnerable to backdoor attacks, typically reliant on heuristic brute-force methods. Despite significant empiri…
Distillation Enhanced Time Series Forecasting Network with Momentum Contrastive Learning
Haozhi Gao, Qianqian Ren, Jinbao Li
Contrastive representation learning is crucial in time series analysis as it alleviates the issue of data noise and incompleteness as well as sparsity of supervision signal. Howeve…
Hybrid Variational Autoencoder for Time Series Forecasting
Borui Cai, Shuiqiao Yang, Longxiang Gao +1
Variational autoencoders (VAE) are powerful generative models that learn the latent representations of input data as random variables. Recent studies show that VAE can flexibly lea…
Deep Reinforcement Learning Microgrid Optimization Strategy Considering Priority Flexible Demand Side
Jinsong Sang, Hongbin Sun, Lei Kou
As an efficient way to integrate multiple distributed energy resources and the user side, a microgrid is mainly faced with the problems of small-scale volatility, uncertainty, inte…
An Efficient and Reliable Asynchronous Federated Learning Scheme for Smart Public Transportation
Chenhao Xu, Youyang Qu, Tom H. Luan +3
Since the traffic conditions change over time, machine learning models that predict traffic flows must be updated continuously and efficiently in smart public transportation. Feder…
Prototype-Guided Memory Replay for Continual Learning
Stella Ho, Ming Liu, Lan Du +2
Continual learning (CL) refers to a machine learning paradigm that learns continuously without forgetting previously acquired knowledge. Thereby, major difficulty in CL is catastro…
SCEI: A Smart-Contract Driven Edge Intelligence Framework for IoT Systems
Chenhao Xu, Jiaqi Ge, Yong Li +5
Federated learning (FL) enables collaborative training of a shared model on edge devices while maintaining data privacy. FL is effective when dealing with independent and identical…
Self-Weighted Robust LDA for Multiclass Classification with Edge Classes
Caixia Yan, Xiaojun Chang, Minnan Luo +4
Linear discriminant analysis (LDA) is a popular technique to learn the most discriminative features for multi-class classification. A vast majority of existing LDA algorithms are p…
A Comprehensive Survey of Neural Architecture Search: Challenges and Solutions
Pengzhen Ren, Yun Xiao, Xiaojun Chang +4
Deep learning has made breakthroughs and substantial in many fields due to its powerful automatic representation capabilities. It has been proven that neural architecture design is…
Discrete Optimal Graph Clustering
Yudong Han, Lei Zhu, Zhiyong Cheng +2
Graph based clustering is one of the major clustering methods. Most of it work in three separate steps: similarity graph construction, clustering label relaxing and label discretiz…
Feature selection in detection of adverse drug reactions from the Health Improvement Network (THIN) database
Yihui Liu, Uwe Aickelin
Adverse drug reaction (ADR) is widely concerned for public health issue. ADRs are one of most common causes to withdraw some drugs from market. Prescription event monitoring (PEM)…