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A 512-nW 0.003-mm2 Forward-Forward Black Box Trainer for an Analog Voice Activity Detector in 28-nm CMOS Journal article
LI JUNDE, XIN GUOQIANG, YU WEI HAN, UN KA FAI, RUI P MARTINS, MAK PUI IN. A 512-nW 0.003-mm2 Forward-Forward Black Box Trainer for an Analog Voice Activity Detector in 28-nm CMOS[J]. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS, 2024, 71(11), 4703-4707.
Authors:  LI JUNDE;  XIN GUOQIANG;  YU WEI HAN;  UN KA FAI;  RUI P MARTINS; et al.
Favorite | TC[WOS]:0 TC[Scopus]:0  IF:4.0/3.7 | Submit date：2024/08/29
Voice Activity Detection  Convolution Neural Network  Edge Learning  Forward-forward Algorithm  Black Box Training  Back Propagation  
DeepTM: Efficient Tensor Management in Heterogeneous Memory for DNN Training Journal article
Zhou, Haoran, Rang, Wei, Chen, Hongyang, Zhou, Xiaobo, Cheng, Dazhao. DeepTM: Efficient Tensor Management in Heterogeneous Memory for DNN Training[J]. IEEE Transactions on Parallel and Distributed Systems, 2024, 35(11), 1920-1935.
Authors:  Zhou, Haoran;  Rang, Wei;  Chen, Hongyang;  Zhou, Xiaobo;  Cheng, Dazhao
Favorite | TC[WOS]:0 TC[Scopus]:0  IF:5.6/4.5 | Submit date：2024/08/05
Deep Neural Network Training  Heterogeneous Memory  Memory Management  Performance Optimization  
Informative Nodes Mining for Class-Imbalanced Representation Learning Journal article
Zhou, Mengting, Gong, Zhiguo. Informative Nodes Mining for Class-Imbalanced Representation Learning[J]. IEEE Transactions on Computational Social Systems, 2024.
Authors:  Zhou, Mengting;  Gong, Zhiguo
Favorite | TC[WOS]:0 TC[Scopus]:0  IF:4.5/4.6 | Submit date：2024/05/16
Class Imbalanced Learning  Costs  Graph Neural Network (Gnn)  Graph Neural Networks  Node Classification  Representation Learning  Social Networking (Online)  Task Analysis  Training  Training Data  
Extreme Fuzzy Broad Learning System: Algorithm, Frequency Principle, and Applications in Classification and Regression Journal article
Duan, Junwei, Yao, Shiyi, Tan, Jiantao, Liu, Yang, Chen, Long, Zhang, Zhen, Chen, C. L.P.. Extreme Fuzzy Broad Learning System: Algorithm, Frequency Principle, and Applications in Classification and Regression[J]. IEEE Transactions on Neural Networks and Learning Systems, 2024.
Authors:  Duan, Junwei;  Yao, Shiyi;  Tan, Jiantao;  Liu, Yang;  Chen, Long; et al.
Favorite | TC[WOS]:2 TC[Scopus]:1  IF:10.2/10.4 | Submit date：2024/05/16
Broad Learning System (Bls)  Classification  Deep Neural Network  Feature Extraction  Frequency Principle  Fuzzy Extreme Learning Machine (Elm)  Learning Systems  Mathematical Models  Neural Networks  Regression  Stacking  Task Analysis  Training  
Stacked Graph Fusion Denoising Autoencoder for Hyperspectral Anomaly Detection Journal article
Zhang, Yongshan, Li, Yijiang, Wang, Xinxin, Jiang, Xinwei, Zhou, Yicong. Stacked Graph Fusion Denoising Autoencoder for Hyperspectral Anomaly Detection[J]. IEEE Geoscience and Remote Sensing Letters, 2024, 21, 5507405.
Authors:  Zhang, Yongshan;  Li, Yijiang;  Wang, Xinxin;  Jiang, Xinwei;  Zhou, Yicong
Favorite | TC[WOS]:0 TC[Scopus]:1  IF:4.0/4.4 | Submit date：2024/07/04
Anomaly Detection  Anomaly Detection  Denoising Autoencoder  Detectors  Geoscience And Remote Sensing  Graph Neural Network  Hyperspectral Imagery  Hyperspectral Imaging  Image Edge Detection  Noise Reduction  Training  
Out-of-Distribution Detection of Unknown False Data Injection Attack With Logit-Normalized Bayesian ResNet Journal article
Feng, Guangxu, Lao, Keng Weng, Chen, Ge. Out-of-Distribution Detection of Unknown False Data Injection Attack With Logit-Normalized Bayesian ResNet[J]. IEEE Transactions on Smart Grid, 2024.
Authors:  Feng, Guangxu;  Lao, Keng Weng;  Chen, Ge
Favorite | TC[WOS]:0 TC[Scopus]:1  IF:8.6/9.6 | Submit date：2024/07/04
Bayes Methods  Bayesian Neural Network  Current Measurement  Deep Learning  Epistemic Uncertainty  False Data Injection Attack  Neural Networks  Out-of-distribution Detection  Training  Uncertainty  Uncertainty Calibration  Vectors  
Denoising Noisy Neural Networks: A Bayesian Approach with Compensation Journal article
Shao,Yulin, Liew,Soung Chang, Gunduz,Deniz. Denoising Noisy Neural Networks: A Bayesian Approach with Compensation[J]. IEEE Transactions on Signal Processing, 2023, 71, 2460 - 2474.
Authors:  Shao,Yulin;  Liew,Soung Chang;  Gunduz,Deniz
Favorite | TC[WOS]:2 TC[Scopus]:5  IF:4.6/5.2 | Submit date：2023/08/03
Denoiser  Estimation  Federated Edge Learning  Maximum Likelihood Estimation  Neural Networks  Noise Measurement  Noise Reduction  Noisy Neural Network  Training  Wireless Communication  Wireless Transmission Of Neural Networks  
Highway Connection for Low-Latency and High-Accuracy Spiking Neural Networks Journal article
Zhang,Anguo, Wu,Junyi, Li,Xiumin, Li,Hung Chun, Gao,Yueming, Pun,Sio Hang. Highway Connection for Low-Latency and High-Accuracy Spiking Neural Networks[J]. IEEE Transactions on Circuits and Systems II: Express Briefs, 2023, 70(12), 4579-4583.
Authors:  Zhang,Anguo;  Wu,Junyi;  Li,Xiumin;  Li,Hung Chun;  Gao,Yueming; et al.
Favorite | TC[WOS]:1 TC[Scopus]:2  IF:4.0/3.7 | Submit date：2023/08/03
Biological Neural Networks  Computational Modeling  Firing  Highway Connection  Inference Response Speed  Membrane Potentials  Neurons  Road Transportation  Spiking Neural Network  Training  
A Simple yet Effective Layered Loss for Pre-training of Network Embedding Journal article
Chen, Junyang, Li, Xueliang, Li, Yuanman, Li, Paul, Wang, Mengzhu, Zhang, Xiang, Gong, Zhiguo, Wu, Kaishun, Leung, Victor C.M.. A Simple yet Effective Layered Loss for Pre-training of Network Embedding[J]. IEEE Transactions on Network Science and Engineering, 2022, 9(3), 1827 - 1837.
Authors:  Chen, Junyang;  Li, Xueliang;  Li, Yuanman;  Li, Paul;  Wang, Mengzhu; et al.
Favorite | TC[WOS]:6 TC[Scopus]:3  IF:6.7/6.0 | Submit date：2022/05/17
Graph Neural Networks  Layered Loss  Network Embedding  Pre-training Of Unlabeled Nodes  
How meta-heuristic algorithms contribute to deep learning in the hype of big data analytics Conference paper
Simon Fong, Suash Deb, Xin-she Yang. How meta-heuristic algorithms contribute to deep learning in the hype of big data analytics[C]:SPRINGER-VERLAG BERLIN, HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY, 2017, 3-25.
Authors:  Simon Fong;  Suash Deb;  Xin-she Yang
Favorite | TC[WOS]:38 TC[Scopus]:49 | Submit date：2019/02/13
Deep Learning  Meta-heuristic Algorithm  Neural Network Training  Nature-inspired Computing Algorithms  Algorithm Design