| An empirical comparison of supervised learning algorithms R Caruana, A Niculescu-Mizil Proceedings of the 23rd international conference on Machine learning, 161-168, 2006 | 4371 | 2006 |
| Model compression C Buciluǎ, R Caruana, A Niculescu-Mizil Proceedings of the 12th ACM SIGKDD international conference on Knowledge …, 2006 | 3603 | 2006 |
| Predicting good probabilities with supervised learning A Niculescu-Mizil, R Caruana Proceedings of the 22nd international conference on Machine learning, 625-632, 2005 | 2489 | 2005 |
| Ensemble selection from libraries of models R Caruana, A Niculescu-Mizil, G Crew, A Ksikes ICML, 2004 | 1313 | 2004 |
| Data mining in metric space: an empirical analysis of supervised learning performance criteria R Caruana, A Niculescu-Mizil Proceedings of the tenth ACM SIGKDD international conference on Knowledge …, 2004 | 480 | 2004 |
| Topic-link LDA: joint models of topic and author community Y Liu, A Niculescu-Mizil, W Gryc proceedings of the 26th annual international conference on machine learning …, 2009 | 456 | 2009 |
| Regret bounds for sleeping experts and bandits R Kleinberg, A Niculescu-Mizil, Y Sharma Machine learning 80 (2), 245-272, 2010 | 302 | 2010 |
| Learning graphical model structure using L1-regularization paths M Schmidt, A Niculescu-Mizil, K Murphy AAAI 7, 1278-1283, 2007 | 302 | 2007 |
| Obtaining Calibrated Probabilities from Boosting. A Niculescu-Mizil, R Caruana UAI 5, 413-20, 2005 | 279 | 2005 |
| Getting the most out of ensemble selection R Caruana, A Munson, A Niculescu-Mizil Sixth International Conference on Data Mining (ICDM'06), 828-833, 2006 | 226 | 2006 |
| Inductive transfer for Bayesian network structure learning A Niculescu-Mizil, R Caruana Artificial intelligence and statistics, 339-346, 2007 | 181* | 2007 |
| Spatial-temporal causal modeling for climate change attribution AC Lozano, H Li, A Niculescu-Mizil, Y Liu, C Perlich, J Hosking, N Abe Proceedings of the 15th ACM SIGKDD international conference on Knowledge …, 2009 | 154 | 2009 |
| PAV and the ROC convex hull T Fawcett, A Niculescu-Mizil Machine Learning 68 (1), 97-106, 2007 | 154 | 2007 |
| Developing predictive models using electronic medical records: challenges and pitfalls C Paxton, A Niculescu-Mizil, S Saria AMIA Annual Symposium Proceedings 2013, 1109, 2013 | 144 | 2013 |
| Winning the KDD cup orange challenge with ensemble selection A Niculescu-Mizil, C Perlich, G Swirszcz, V Sindhwani, Y Liu, P Melville, ... KDD-Cup 2009 competition, 23-34, 2009 | 91 | 2009 |
| Learning temporal causal graphs for relational time-series analysis Y Liu, A Niculescu-Mizil, AC Lozano, Y Lu Proceedings of the 27th International Conference on Machine Learning (ICML …, 2010 | 77 | 2010 |
| Adaptive Convolutional Neural Knowledge Graph Learning System Leveraging Entity Descriptions R Min, B Bai, A Niculescu-Mizil, I Durdanovic, HP Graf US Patent App. 16/168,244, 2019 | 72 | 2019 |
| A binary classification framework for two-stage multiple kernel learning A Kumar, A Niculescu-Mizil, K Kavukcuoglu, H Daume III arXiv preprint arXiv:1206.6428, 2012 | 72 | 2012 |
| Modeling and analytics for cyber-physical systems in the age of big data AB Sharma, F Ivančić, A Niculescu-Mizil, H Chen, G Jiang ACM SIGMETRICS Performance Evaluation Review 41 (4), 74-77, 2014 | 68 | 2014 |
| Bayesian models for large-scale hierarchical classification S Gopal, Y Yang, B Bai, A Niculescu-Mizil Advances in Neural Information Processing Systems 25, 2012 | 64 | 2012 |
Yan LiuProfessor, Director of Machine Learning Center@USCVerified email at usc.edu
