| Online bagging and boosting NC Oza, SJ Russell International workshop on artificial intelligence and statistics, 229-236, 2001 | 1320 | 2001 |
| Classifier ensembles: Select real-world applications NC Oza, K Tumer Information fusion 9 (1), 4-20, 2008 | 437 | 2008 |
| Experimental comparisons of online and batch versions of bagging and boosting NC Oza, S Russell Proceedings of the seventh ACM SIGKDD international conference on Knowledge …, 2001 | 323 | 2001 |
| Multiple kernel learning for heterogeneous anomaly detection: algorithm and aviation safety case study S Das, BL Matthews, AN Srivastava, NC Oza Proceedings of the 16th ACM SIGKDD international conference on Knowledge …, 2010 | 309 | 2010 |
| Online ensemble learning NC Oza, S Russell University of California, Berkeley, 2001 | 301 | 2001 |
| Facing the reality of data stream classification: coping with scarcity of labeled data MM Masud, C Woolam, J Gao, L Khan, J Han, KW Hamlen, NC Oza Knowledge and information systems 33, 213-244, 2012 | 179 | 2012 |
| Classification and adaptive novel class detection of feature-evolving data streams MM Masud, Q Chen, L Khan, CC Aggarwal, J Gao, J Han, A Srivastava, ... IEEE Transactions on Knowledge and Data Engineering 25 (7), 1484-1497, 2012 | 171 | 2012 |
| Input decimation ensembles: Decorrelation through dimensionality reduction NC Oza, K Tumer International Workshop on Multiple Classifier Systems, 238-247, 2001 | 133 | 2001 |
| Input decimated ensembles K Tumer, NC Oza Pattern Analysis & Applications 6, 65-77, 2003 | 111 | 2003 |
| Unsupervised anomaly detection for liquid-fueled rocket propulsion health monitoring M Schwabacher, N Oza, B Matthews Journal of aerospace computing, information, and communication 6 (7), 464-482, 2009 | 93 | 2009 |
| Discovering anomalous aviation safety events using scalable data mining algorithms B Matthews, S Das, K Bhaduri, K Das, R Martin, N Oza Journal of Aerospace Information Systems 10 (10), 467-475, 2013 | 83 | 2013 |
| Outlook for exploiting artificial intelligence in the earth and environmental sciences SA Boukabara, V Krasnopolsky, SG Penny, JQ Stewart, A McGovern, ... Bulletin of the American Meteorological Society 102 (5), E1016-E1032, 2021 | 78 | 2021 |
| Boosting with averaged weight vectors NC Oza International Workshop on Multiple Classifier Systems, 15-24, 2003 | 76 | 2003 |
| Decimated input ensembles for improved generalization K Turner, NC Oza IJCNN'99. International Joint Conference on Neural Networks. Proceedings …, 1999 | 73 | 1999 |
| Topic modeling for OLAP on multidimensional text databases: topic cube and its applications D Zhang, CX Zhai, J Han, A Srivastava, N Oza Statistical Analysis and Data Mining: The ASA Data Science Journal 2 (5‐6 …, 2009 | 69 | 2009 |
| Classification of aeronautics system health and safety documents N Oza, JP Castle, J Stutz IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and …, 2009 | 68 | 2009 |
| Aveboost2: Boosting for noisy data NC Oza International workshop on multiple classifier systems, 31-40, 2004 | 61 | 2004 |
| Semi-Markov switching vector autoregressive model-based anomaly detection in aviation systems I Melnyk, A Banerjee, B Matthews, N Oza Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge …, 2016 | 60 | 2016 |
| Vector autoregressive model-based anomaly detection in aviation systems I Melnyk, B Matthews, H Valizadegan, A Banerjee, N Oza Journal of Aerospace Information Systems 13 (4), 161-173, 2016 | 59 | 2016 |
| Virtual sensors: Using data mining techniques to efficiently estimate remote sensing spectra AN Srivastava, NC Oza, J Stroeve IEEE Transactions on Geoscience and Remote Sensing 43 (3), 590-600, 2005 | 57 | 2005 |
