| Training deep neural networks on imbalanced data sets S Wang, W Liu, J Wu, L Cao, Q Meng, PJ Kennedy 2016 International Joint Conference on Neural Networks (IJCNN), 4368-4374, 2016 | 574 | 2016 |
| Discovering spatio-temporal causal interactions in traffic data streams W Liu, Y Zheng, S Chawla, J Yuan, X Xing Proceedings of the 17th ACM SIGKDD international conference on Knowledge …, 2011 | 481 | 2011 |
| Attention-based transactional context embedding for next-item recommendation S Wang, L Hu, L Cao, X Huang, D Lian, W Liu Thirty-Second AAAI Conference on Artificial Intelligence, 2018 | 261 | 2018 |
| Class confidence weighted knn algorithms for imbalanced data sets W Liu, S Chawla Pacific-Asia Conference on Knowledge Discovery and Data Mining, 345-356, 2011 | 210 | 2011 |
| A robust decision tree algorithm for imbalanced data sets W Liu, S Chawla, DA Cieslak, NV Chawla Proceedings of the 2010 SIAM International Conference on Data Mining, 766-777, 2010 | 210 | 2010 |
| Learning a Mixture of Granularity-Specific Experts for Fine-Grained Categorization L Zhang, S Huang, W Liu, D Tao Proceedings of the IEEE International Conference on Computer Vision, 8331-8340, 2019 | 199 | 2019 |
| On detection of emerging anomalous traffic patterns using GPS data LX Pang, S Chawla, W Liu, Y Zheng Data & Knowledge Engineering 87, 357-373, 2013 | 182 | 2013 |
| A survey on canonical correlation analysis X Yang, W Liu, W Liu, D Tao IEEE Transactions on Knowledge and Data Engineering 33 (6), 2349-2368, 2019 | 159 | 2019 |
| Discovering congestion propagation patterns in spatio-temporal traffic data H Nguyen, W Liu, F Chen IEEE Transactions on Big Data 3 (2), 169-180, 2017 | 140 | 2017 |
| On mining anomalous patterns in road traffic streams L Pang, S Chawla, W Liu, Y Zheng Advanced Data Mining and Applications, 237-251, 2011 | 122 | 2011 |
| Ensemble-based wrapper methods for feature selection and class imbalance learning P Yang, W Liu, BB Zhou, S Chawla, AY Zomaya | 104* | |
| A game theoretical model for adversarial learning W Liu, S Chawla 2009 IEEE International Conference on Data Mining Workshops, 25-30, 2009 | 92 | 2009 |
| Online spatio-temporal crowd flow distribution prediction for complex metro system Y Gong, Z Li, J Zhang, W Liu, Y Zheng IEEE Transactions on knowledge and data engineering 34 (2), 865-880, 2020 | 91 | 2020 |
| Spatio-temporal outlier detection in precipitation data E Wu, W Liu, S Chawla Knowledge Discovery from Sensor Data, 115-133, 2010 | 88 | 2010 |
| Mining adversarial patterns via regularized loss minimization W Liu, S Chawla Machine learning 81, 69-83, 2010 | 74 | 2010 |
| Network-wide Crowd Flow Prediction of Sydney Trains via Customized Online Non-negative Matrix Factorization Y Gong, Z Li, J Zhang, W Liu, Y Zheng, C Kirsch Proceedings of the 27th ACM International Conference on Information and …, 2018 | 68 | 2018 |
| Bayesian Tensor Inference for Sketch-Based Facial Photo Hallucination. W Liu, X Tang, J Liu IJCAI, 2141-2146, 2007 | 68 | 2007 |
| DeepCU: integrating both common and unique latent information for multimodal sentiment analysis S Verma, C Wang, L Zhu, W Liu Proceedings of the 28th International Joint Conference on Artificial …, 2019 | 57 | 2019 |
| Multi-Label Feature Selection using Correlation Information A Braytee, W Liu, DR Catchpoole, PJ Kennedy Proceedings of the 2017 ACM on Conference on Information and Knowledge …, 2017 | 54 | 2017 |
| Time Series Forecasting using Distribution Enhanced Linear Regression G Ristanoski, W Liu, J Bailey | 52* | |
sanjay chawlaQatar Computing Research Institute, HBKUVerified email at sydney.edu.au
