| Outlier detection with autoencoder ensembles J Chen, S Sathe, C Aggarwal, D Turaga Proceedings of the 2017 SIAM international conference on data mining, 90-98, 2017 | 598 | 2017 |
| Theoretical Foundations and Algorithms for Outlier Ensembles CC Aggarwal, S Sathe ACM SIGKDD Explorations Newsletter 17 (1), 24-47, 2015 | 338 | 2015 |
| Opensense: open community driven sensing of environment K Aberer, S Sathe, D Chakraborty, A Martinoli, G Barrenetxea, B Faltings, ... Proceedings of the ACM SIGSPATIAL international workshop on GeoStreaming, 39-42, 2010 | 170 | 2010 |
| Subspace outlier detection in linear time with randomized hashing S Sathe, CC Aggarwal 2016 IEEE 16th International Conference on Data Mining (ICDM), 459-468, 2016 | 103 | 2016 |
| LODES: Local density meets spectral outlier detection S Sathe, C Aggarwal Proceedings of the 2016 SIAM international conference on data mining, 171-179, 2016 | 78 | 2016 |
| A survey of model-based sensor data acquisition and management S Sathe, TG Papaioannou, H Jeung, K Aberer Managing and mining sensor data, 9-50, 2013 | 73 | 2013 |
| Kernelized matrix factorization for collaborative filtering X Liu, C Aggarwal, YF Li, X Kong, X Sun, S Sathe Proceedings of the 2016 SIAM international conference on data mining, 378-386, 2016 | 71 | 2016 |
| Twitter analytics: a big data management perspective O Goonetilleke, T Sellis, X Zhang, S Sathe ACM SIGKDD Explorations Newsletter 16 (1), 11-20, 2014 | 68 | 2014 |
| Effective metadata management in federated sensor networks H Jeung, S Sarni, I Paparrizos, S Sathe, K Aberer, N Dawes, ... 2010 IEEE International Conference on Sensor Networks, Ubiquitous, and …, 2010 | 55 | 2010 |
| Subspace histograms for outlier detection in linear time S Sathe, CC Aggarwal Knowledge and Information Systems 56, 691-715, 2018 | 40 | 2018 |
| Managing evolving uncertainty in trajectory databases H Jeung, H Lu, S Sathe, ML Yiu IEEE Transactions on Knowledge and Data Engineering 26 (7), 1692-1705, 2013 | 38 | 2013 |
| Similarity forests S Sathe, CC Aggarwal Proceedings of the 23rd ACM SIGKDD international conference on knowledge …, 2017 | 34 | 2017 |
| Improving spectral clustering with deep embedding and cluster estimation L Duan, C Aggarwal, S Ma, S Sathe 2019 IEEE International Conference on Data Mining (ICDM), 170-179, 2019 | 30 | 2019 |
| Fast distributed correlation discovery over streaming time-series data T Guo, S Sathe, K Aberer Proceedings of the 24th ACM International on Conference on Information and …, 2015 | 26 | 2015 |
| Creating probabilistic databases from imprecise time-series data S Sathe, H Jeung, K Aberer 2011 IEEE 27th International Conference on Data Engineering, 327-338, 2011 | 25 | 2011 |
| Improving spectral clustering with deep embedding, cluster estimation and metric learning L Duan, S Ma, C Aggarwal, S Sathe Knowledge and Information Systems 63, 675-694, 2021 | 18 | 2021 |
| Towards enabling probabilistic databases for participatory sensing NQV Hung, S Sathe, DC Thang, K Aberer 10th IEEE International Conference on Collaborative Computing: Networking …, 2014 | 18 | 2014 |
| Rumor spreading in LiveJournal S Sathe | 18 | 2008 |
| AFFINITY: Efficiently querying statistical measures on time-series data S Sathe, K Aberer 2013 IEEE 29th International Conference on Data Engineering (ICDE), 841-852, 2013 | 17 | 2013 |
| Nearest neighbor classifiers versus random forests and support vector machines S Sathe, CC Aggarwal 2019 IEEE International Conference on Data Mining (ICDM), 1300-1305, 2019 | 13 | 2019 |
Charu AggarwalDistinguished Research Staff Member, IBM T. J. Watson Research CenterVerified email at us.ibm.com
