| Robust log-based anomaly detection on unstable log data X Zhang, Y Xu, Q Lin, B Qiao, H Zhang, Y Dang, C Xie, X Yang, Q Cheng, ... Proceedings of the 2019 27th ACM joint meeting on European software …, 2019 | 582 | 2019 |
| An incremental network for on-line unsupervised classification and topology learning S Furao, O Hasegawa Neural networks 19 (1), 90-106, 2006 | 428 | 2006 |
| Image data augmentation for deep learning: A survey S Yang, W Xiao, M Zhang, S Guo, J Zhao, F Shen arXiv preprint arXiv:2204.08610, 2022 | 325 | 2022 |
| Forecasting exchange rate using deep belief networks and conjugate gradient method F Shen, J Chao, J Zhao Neurocomputing 167, 243-253, 2015 | 294 | 2015 |
| An enhanced self-organizing incremental neural network for online unsupervised learning S Furao, T Ogura, O Hasegawa Neural Networks 20 (8), 893-903, 2007 | 288 | 2007 |
| A fast nearest neighbor classifier based on self-organizing incremental neural network F Shen, O Hasegawa Neural networks 21 (10), 1537-1547, 2008 | 148 | 2008 |
| A fast no search fractal image coding method S Furao, O Hasegawa Signal Processing: Image Communication 19 (5), 393-404, 2004 | 136 | 2004 |
| An online incremental learning support vector machine for large-scale data J Zheng, F Shen, H Fan, J Zhao Neural Computing and Applications 22, 1023-1035, 2013 | 127 | 2013 |
| Cross-dataset time series anomaly detection for cloud systems X Zhang, J Kim, Q Lin, K Lim, SO Kanaujia, Y Xu, K Jamieson, ... 2019 USENIX Annual Technical Conference (USENIX ATC 19), 1063-1076, 2019 | 88 | 2019 |
| Operation-aware neural networks for user response prediction Y Yang, B Xu, S Shen, F Shen, J Zhao Neural Networks 121, 161-168, 2020 | 81 | 2020 |
| An adaptive incremental LBG for vector quantization F Shen, O Hasegawa Neural Networks 19 (5), 694-704, 2006 | 76 | 2006 |
| Forecasting exchange rate with deep belief networks J Chao, F Shen, J Zhao The 2011 International Joint Conference on Neural Networks, 1259-1266, 2011 | 71 | 2011 |
| An incremental online semi-supervised active learning algorithm based on self-organizing incremental neural network F Shen, H Yu, K Sakurai, O Hasegawa Neural Computing and Applications 20, 1061-1074, 2011 | 63 | 2011 |
| Time series forecasting using GRU neural network with multi-lag after decomposition X Zhang, F Shen, J Zhao, GH Yang Neural Information Processing: 24th International Conference, ICONIP 2017 …, 2017 | 62 | 2017 |
| A model with fuzzy granulation and deep belief networks for exchange rate forecasting R Zhang, F Shen, J Zhao 2014 international joint conference on neural networks (IJCNN), 366-373, 2014 | 56 | 2014 |
| Temporal convolutional attention-based network for sequence modeling H Hao, Y Wang, S Xue, Y Xia, J Zhao, F Shen arXiv preprint arXiv:2002.12530, 2020 | 53 | 2020 |
| A general associative memory based on self-organizing incremental neural network F Shen, Q Ouyang, W Kasai, O Hasegawa Neurocomputing 104, 57-71, 2013 | 51 | 2013 |
| An incremental learning vector quantization algorithm for pattern classification Y Xu, F Shen, J Zhao Neural Computing and Applications 21, 1205-1215, 2012 | 51 | 2012 |
| A parallel computing platform for training large scale neural networks R Gu, F Shen, Y Huang 2013 IEEE international conference on big data, 376-384, 2013 | 47 | 2013 |
| Image clustering via deep embedded dimensionality reduction and probability-based triplet loss Y Yan, H Hao, B Xu, J Zhao, F Shen IEEE Transactions on Image Processing 29, 5652-5661, 2020 | 43 | 2020 |
Ye XuMetaVerified email at meta.com
