Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
The nature of statistical learning theory
The nature of statistical learning theory
Least Squares Support Vector Machine Classifiers
Neural Processing Letters
Duality and Geometry in SVM Classifiers
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
A lower bound on the performance of the quadratic discriminant function
Journal of Multivariate Analysis
Learning large margin classifiers locally and globally
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Nonparametric classification with polynomial MPMC cascades
ICML '04 Proceedings of the twenty-first international conference on Machine learning
The Minimum Error Minimax Probability Machine
The Journal of Machine Learning Research
Second Order Cone Programming Formulations for Feature Selection
The Journal of Machine Learning Research
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
Pareto optimal linear classification
ICML '06 Proceedings of the 23rd international conference on Machine learning
Clustering based large margin classification: a scalable approach using SOCP formulation
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
A Semidefinite Programming Approach to Optimal-Moment Bounds for Convex Classes of Distributions
Mathematics of Operations Research
A Direct Method for Building Sparse Kernel Learning Algorithms
The Journal of Machine Learning Research
Second Order Cone Programming Approaches for Handling Missing and Uncertain Data
The Journal of Machine Learning Research
Structured large margin machines: sensitive to data distributions
Machine Learning
A comparative study of Minimax Probability Machine-based approaches for face recognition
Pattern Recognition Letters
Knowledge and Information Systems
Robust multiclass kernel-based classifiers
Computational Optimization and Applications
Multi-class Discriminant Kernel Learning via Convex Programming
The Journal of Machine Learning Research
An efficient kernel matrix evaluation measure
Pattern Recognition
Kernel Maximum a Posteriori Classification with Error Bound Analysis
Neural Information Processing
A One-Step Network Traffic Prediction
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence
Structural Support Vector Machine
ISNN '08 Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks
Interval Data Classification under Partial Information: A Chance-Constraint Approach
PAKDD '09 Proceedings of the 13th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
Cutting-set methods for robust convex optimization with pessimizing oracles
Optimization Methods & Software
A novel kernel-based maximum a posteriori classification method
Neural Networks
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Reducing the risk of query expansion via robust constrained optimization
Proceedings of the 18th ACM conference on Information and knowledge management
Recursive Bayesian linear regression for adaptive classification
IEEE Transactions on Signal Processing
Kernel methods for short-term portfolio management
Expert Systems with Applications: An International Journal
Robustness and Regularization of Support Vector Machines
The Journal of Machine Learning Research
Exploiting uncertain data in support vector classification
KES'07/WIRN'07 Proceedings of the 11th international conference, KES 2007 and XVII Italian workshop on neural networks conference on Knowledge-based intelligent information and engineering systems: Part III
Sparse learning for support vector classification
Pattern Recognition Letters
Soft fuzzy rough sets for robust feature evaluation and selection
Information Sciences: an International Journal
Constructing nonlinear discriminants from multiple data views
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part I
Learning classifiers from imbalanced data based on biased minimax probability machine
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
IEEE Transactions on Information Theory
Classifier evaluation and attribute selection against active adversaries
Data Mining and Knowledge Discovery
Learning with uncertain kernel matrix set
Journal of Computer Science and Technology
Robust kernel-based regression
CIMMACS'05 Proceedings of the 4th WSEAS international conference on Computational intelligence, man-machine systems and cybernetics
Stackelberg games for adversarial prediction problems
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Robust fuzzy rough classifiers
Fuzzy Sets and Systems
Theory and Applications of Robust Optimization
SIAM Review
Actor based video indexing and retrieval using visual information
ICNC'06 Proceedings of the Second international conference on Advances in Natural Computation - Volume Part II
A multiclass classification method based on output design
PAKDD'06 Proceedings of the 10th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
A Distributional Interpretation of Robust Optimization
Mathematics of Operations Research
ICONIP'06 Proceedings of the 13 international conference on Neural Information Processing - Volume Part I
A multiclass classification framework for document categorization
DAS'06 Proceedings of the 7th international conference on Document Analysis Systems
Manifold-Regularized minimax probability machine
PSL'11 Proceedings of the First IAPR TC3 conference on Partially Supervised Learning
Twin Mahalanobis distance-based support vector machines for pattern recognition
Information Sciences: an International Journal
Learning SVM with weighted maximum margin criterion for classification of imbalanced data
Mathematical and Computer Modelling: An International Journal
Adversarial support vector machine learning
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
A minimax probabilistic approach to feature transformation for multi-class data
Applied Soft Computing
Semi-supervised discriminatively regularized classifier with pairwise constraints
PRICAI'12 Proceedings of the 12th Pacific Rim international conference on Trends in Artificial Intelligence
Hybrid classifiers for object classification with a rich background
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part V
Training mahalanobis kernels by linear programming
ICANN'12 Proceedings of the 22nd international conference on Artificial Neural Networks and Machine Learning - Volume Part II
Fuzzy one-class classification model using contamination neighborhoods
Advances in Fuzzy Systems
Scientific and Technical Information Processing
Hyperdisk based large margin classifier
Pattern Recognition
Three-fold structured classifier design based on matrix pattern
Pattern Recognition
A unified classification model based on robust optimization
Neural Computation
Structural twin support vector machine for classification
Knowledge-Based Systems
Robust novelty detection in the framework of a contamination neighbourhood
International Journal of Intelligent Information and Database Systems
Robust novelty detection in the framework of a contamination neighbourhood
International Journal of Intelligent Information and Database Systems
Structural twin parametric-margin support vector machine for binary classification
Knowledge-Based Systems
Static prediction games for adversarial learning problems
The Journal of Machine Learning Research
A second order cone programming approach for semi-supervised learning
Pattern Recognition
Laplacian minimax probability machine
Pattern Recognition Letters
Conjugate relation between loss functions and uncertainty sets in classification problems
The Journal of Machine Learning Research
Alternative second-order cone programming formulations for support vector classification
Information Sciences: an International Journal
Hi-index | 0.07 |
When constructing a classifier, the probability of correct classification of future data points should be maximized. We consider a binary classification problem where the mean and covariance matrix of each class are assumed to be known. No further assumptions are made with respect to the class-conditional distributions. Misclassification probabilities are then controlled in a worst-case setting: that is, under all possible choices of class-conditional densities with given mean and covariance matrix, we minimize the worst-case (maximum) probability of misclassification of future data points. For a linear decision boundary, this desideratum is translated in a very direct way into a (convex) second order cone optimization problem, with complexity similar to a support vector machine problem. The minimax problem can be interpreted geometrically as minimizing the maximum of the Mahalanobis distances to the two classes. We address the issue of robustness with respect to estimation errors (in the means and covariances of the classes) via a simple modification of the input data. We also show how to exploit Mercer kernels in this setting to obtain nonlinear decision boundaries, yielding a classifier which proves to be competitive with current methods, including support vector machines. An important feature of this method is that a worst-case bound on the probability of misclassification of future data is always obtained explicitly.