| Cloud Motion Estimation for Short Term Solar Irradiation Prediction H Huang, J Xu, Z Peng, S Yoo, D Yu, D Huang, H Qin Smart Grid Communications (SmartGridComm), 2013 IEEE International Conference, 2013 | 87 | 2013 |
| Streaming anomaly detection using randomized matrix sketching H Huang, S Kasiviswanathan Proceedings of the VLDB Endowment 9 (3), 192-203, 2015 | 65 | 2015 |
| Unsupervised feature selection on data streams H Huang, S Yoo, SP Kasiviswanathan the 24th ACM International on Conference on Information and Knowledge Management, 2015 | 50 | 2015 |
| Scalable causal graph learning through a deep neural network C Xu, H Huang, S Yoo Proceedings of the 28th ACM international conference on information and …, 2019 | 46 | 2019 |
| Correlation and Local Feature based Cloud Motion Estimation H Huang, S Yoo, D Yu, D Huang, H Qin KDD Multimedia Data Mining (KDD/MDM) workshop, 2012 | 35 | 2012 |
| Streaming Spectral Clustering S Yoo, H Huang, SP Kasiviswanathan IEEE ICDE 2016, 2016 | 28 | 2016 |
| The solution structures of two soybean calmodulin isoforms provide a structural basis for their selective target activation properties H Ishida, H Huang, AP Yamniuk, Y Takaya, HJ Vogel Journal of Biological Chemistry 283 (21), 14619-14628, 2008 | 27 | 2008 |
| Physics-based Anomaly Detection Defined on Manifold Space H Huang, H Qin, S Yoo, D Yu ACM Transactions on Knowledge Discovery from Data (TKDD), 2014 | 24 | 2014 |
| A Robust Clustering Algorithm based on Ag- gregated Heat Kernel Mapping H Huang, S Yoo, H Qin, D Yu IEEE 11th International Conference on Data Mining, 2011 | 22 | 2011 |
| The solution structure of the Mg2+ form of soybean calmodulin isoform 4 reveals unique features of plant calmodulins in resting cells H Huang, H Ishida, HJ Vogel Protein Science 19 (3), 475-485, 2010 | 20 | 2010 |
| System and method for unsupervised anomaly detection on industrial time-series data A Harpale, AK Pandey, A Narkaj, AT Graf, H Huang US Patent App. 15/474,563, 2017 | 19 | 2017 |
| Cloud Motion Detection for Short Term Solar Power Prediction H Huang, S Yoo, D Yu, D Huang, H Qin ICML 2011 Workshop on Machine Learning for Global Challenges, 2011 | 17 | 2011 |
| Imbalanced time series classification for flight data analyzing with nonlinear granger causality learning H Huang, C Xu, S Yoo, W Yan, T Wang, F Xue Proceedings of the 29th ACM International Conference on Information …, 2020 | 16 | 2020 |
| Local Anomaly Descriptor: A Robust Unsuper- vised Algorithm for Anomaly Detection based on Diffusion Space H Huang, H Qin, S Yoo, D Yu Proceedings of the 21st ACM international conference on Information and …, 2012 | 16 | 2012 |
| Locality-preserving l1-graph and its application in clustering S Han, H Huang, H Qin, D Yu Proceedings of the 30th Annual ACM Symposium on Applied Computing, 2015 | 15 | 2015 |
| Diverse Power Iteration Embeddings and Its Applications H Huang, S Yoo, D Yu, H Qin IEEE International Conference on Data Mining, 2014 | 15 | 2014 |
| A New Anomaly Detection Algorithm based on Quantum Mechanics H Huang, H Qin, S Yoo, D Yu IEEE 12th International Conference on Data Mining, 2012 | 15 | 2012 |
| A deep neural network for multivariate time series clustering with result interpretation C Xu, H Huang, S Yoo 2021 International Joint Conference on Neural Networks (IJCNN), 1-8, 2021 | 11 | 2021 |
| Label rectification and classification/prediction for multivariate time series data H Huang, X Wang US Patent 10,417,083, 2019 | 11 | 2019 |
| Redundant features removal for unsupervised spectral feature selection algorithms: An empirical study based on nonparametric sparse feature graph P Xu, S Han, H Huang, H Qin International Journal of Data Science and Analytics 8, 77-93, 2019 | 10 | 2019 |
