Hamed Masnadi-Shirazi
Hamed Masnadi-Shirazi
Unknown affiliation
Verified email at ucsd.edu - Homepage
Title
Cited by
Cited by
Year
Cost-sensitive boosting
H Masnadi-Shirazi, N Vasconcelos
IEEE Transactions on pattern analysis and machine intelligence 33 (2), 294-309, 2010
1682010
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, 1049-1056, 2009
1612009
Asymmetric boosting
H Masnadi-Shirazi, N Vasconcelos
Proceedings of the 24th international conference on Machine learning, 609-619, 2007
1172007
Risk minimization, probability elicitation, and cost-sensitive SVMs.
H Masnadi-Shirazi, N Vasconcelos
ICML, 759-766, 2010
822010
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
702010
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
342007
Taylorboost: First and second-order boosting algorithms with explicit margin control
MJ Saberian, H Masnadi-Shirazi, N Vasconcelos
CVPR 2011, 2929-2934, 2011
312011
Cost-sensitive support vector machines
H Masnadi-Shirazi, N Vasconcelos, A Iranmehr
arXiv preprint arXiv:1212.0975, 2012
302012
Cost-sensitive support vector machines
A Iranmehr, H Masnadi-Shirazi, N Vasconcelos
Neurocomputing 343, 50-64, 2019
252019
Variable margin losses for classifier design
H Masnadi-Shirazi, N Vasconcelos
Advances in Neural Information Processing Systems, 1576-1584, 2010
92010
The design of Bayes consistent loss functions for classification
H Masnadi-Shirazi
UC San Diego, 2011
72011
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
62015
Adaboost face detection
H Masnadi-Shirazi
Department of Electoral and Computer Engineering at the University of …, 2004
32004
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
22017
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
12019
Combining Forecasts Using Ensemble Learning
H Masnadi-Shirazi
arXiv preprint arXiv:1707.02430, 2017
2017
Kernel Two-Sample Hypothesis Testing Using Kernel Set Classification
H Masnadi-Shirazi
arXiv preprint arXiv:1706.05612, 2017
2017
Refinement revisited with connections to Bayes error, conditional entropy and calibrated classifiers
H Masnadi-Shirazi
arXiv preprint arXiv:1303.2517, 2013
2013
Predictive Filters Analysis: a supervised approach to analyze EEG data
J Rapela, KK Delgado, S Makeig, H Masnadi-Shirazi, N Vasconcelos
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Articles 1–19