| On the design of loss functions for classification: theory, robustness to outliers, and savageboost H Masnadi-Shirazi, N Vasconcelos Advances in neural information processing systems 21, 2008 | 256 | 2008 |
| Cost-sensitive boosting H Masnadi-Shirazi, N Vasconcelos IEEE Transactions on pattern analysis and machine intelligence 33 (2), 294-309, 2010 | 220 | 2010 |
| Cost-sensitive support vector machines A Iranmehr, H Masnadi-Shirazi, N Vasconcelos Neurocomputing 343, 50-64, 2019 | 169 | 2019 |
| Asymmetric boosting H Masnadi-Shirazi, N Vasconcelos Proceedings of the 24th international conference on Machine learning, 609-619, 2007 | 127 | 2007 |
| Risk minimization, probability elicitation, and cost-sensitive SVMs. H Masnadi-Shirazi, N Vasconcelos ICML, 759-766, 2010 | 114 | 2010 |
| On the design of robust classifiers for computer vision H Masnadi-Shirazi, V Mahadevan, N Vasconcelos 2010 IEEE Computer Society Conference on Computer Vision and Pattern …, 2010 | 88 | 2010 |
| Cost-sensitive support vector machines H Masnadi-Shirazi, N Vasconcelos, A Iranmehr arXiv preprint arXiv:1212.0975, 2012 | 48 | 2012 |
| High detection-rate cascades for real-time object detection H Masnadi-Shirazi, N Vasconcelos 2007 IEEE 11th International Conference on Computer Vision, 1-6, 2007 | 37 | 2007 |
| Taylorboost: First and second-order boosting algorithms with explicit margin control MJ Saberian, H Masnadi-Shirazi, N Vasconcelos CVPR 2011, 2929-2934, 2011 | 36 | 2011 |
| A view of margin losses as regularizers of probability estimates H Masnadi-Shirazi, N Vasconcelos The Journal of Machine Learning Research 16 (1), 2751-2795, 2015 | 15 | 2015 |
| Variable margin losses for classifier design H Masnadi-Shirazi, N Vasconcelos Advances in Neural Information Processing Systems 23, 2010 | 12 | 2010 |
| The design of Bayes consistent loss functions for classification H Masnadi-Shirazi UC San Diego, 2011 | 10 | 2011 |
| A Step by Step Mathematical Derivation and Tutorial on Kalman Filters H Masnadi-Shirazi, A Masnadi-Shirazi, MA Dastgheib arXiv preprint arXiv:1910.03558, 2019 | 8 | 2019 |
| Adaboost face detection H Masnadi-Shirazi Computer Engineering, 2018 | 4 | 2018 |
| Strictly proper kernel scoring rules and divergences with an application to kernel two-sample hypothesis testing H Masnadi-Shirazi arXiv preprint arXiv:1704.02578, 2017 | 2 | 2017 |
| Combining Forecasts Using Ensemble Learning H Masnadi-Shirazi arXiv preprint arXiv:1707.02430, 2017 | 1 | 2017 |
| Refinement revisited with connections to Bayes error, conditional entropy and calibrated classifiers H Masnadi-Shirazi arXiv preprint arXiv:1303.2517, 2013 | 1 | 2013 |
| Kernel Two-Sample Hypothesis Testing Using Kernel Set Classification H Masnadi-Shirazi arXiv preprint arXiv:1706.05612, 2017 | | 2017 |
| Minimizing the Minimum Risk with Applications to Feature Selection, Classification and Kernel Two-Sample Hypothesis Testing H Masnadi-Shirazi | | |
| Predictive Filters Analysis: a supervised approach to analyze EEG data J Rapela, KK Delgado, S Makeig, H Masnadi-Shirazi, N Vasconcelos | | |
Nuno VasconcelosProfessor of Electrical and Computer Engineering, University of California San Diego在 ece.ucsd.edu 的电子邮件经过验证
