Making large-scale support vector machine learning practical
Advances in kernel methods
Fast training of support vector machines using sequential minimal optimization
Advances in kernel methods
Polynomial-Time Decomposition Algorithms for Support Vector Machines
Machine Learning
Training v-support vector regression: theory and algorithms
Neural Computation
Automatic Hyperparameter Tuning for Support Vector Machines
ICANN '02 Proceedings of the International Conference on Artificial Neural Networks
A New Cache Replacement Algorithm in SMO
SVM '02 Proceedings of the First International Workshop on Pattern Recognition with Support Vector Machines
SVM '02 Proceedings of the First International Workshop on Pattern Recognition with Support Vector Machines
Fast SVM Training Algorithm with Decomposition on Very Large Data Sets
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast Kernel Classifiers with Online and Active Learning
The Journal of Machine Learning Research
Support Vector Ordinal Regression
Neural Computation
QP Algorithms with Guaranteed Accuracy and Run Time for Support Vector Machines
The Journal of Machine Learning Research
Maximum-Gain Working Set Selection for SVMs
The Journal of Machine Learning Research
Parallel Software for Training Large Scale Support Vector Machines on Multiprocessor Systems
The Journal of Machine Learning Research
General Polynomial Time Decomposition Algorithms
The Journal of Machine Learning Research
On the complexity of working set selection
Theoretical Computer Science
Machine learning: a review of classification and combining techniques
Artificial Intelligence Review
Expert Systems with Applications: An International Journal
Some Progress of Supervised Learning
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence
A support vector machine with integer parameters
Neurocomputing
Quadratic programming formulations for classificationand regression
Optimization Methods & Software - THE JOINT EUROPT-OMS CONFERENCE ON OPTIMIZATION, 4-7 JULY, 2007, PRAGUE, CZECH REPUBLIC, PART II
An active set quasi-Newton method with projected search for bound constrained minimization
Computers & Mathematics with Applications
Supervised Machine Learning: A Review of Classification Techniques
Proceedings of the 2007 conference on Emerging Artificial Intelligence Applications in Computer Engineering: Real Word AI Systems with Applications in eHealth, HCI, Information Retrieval and Pervasive Technologies
Decomposition Algorithms for Training Large-Scale Semiparametric Support Vector Machines
ECML PKDD '09 Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part II
A convergent hybrid decomposition algorithm model for SVM training
IEEE Transactions on Neural Networks
Gaps in support vector optimization
COLT'07 Proceedings of the 20th annual conference on Learning theory
Generalized SMO-style decomposition algorithms
COLT'07 Proceedings of the 20th annual conference on Learning theory
Linear support vector machine based on variational inequality
ICNC'09 Proceedings of the 5th international conference on Natural computation
Computational Optimization and Applications
Convergence of a new decomposition algorithm for support vector machines
ICIC'06 Proceedings of the 2006 international conference on Intelligent computing: Part II
A sequential minimal optimization algorithm for the all-distances support vector machine
CIARP'10 Proceedings of the 15th Iberoamerican congress conference on Progress in pattern recognition, image analysis, computer vision, and applications
Fast support vector training by Newton's method
ICANN'11 Proceedings of the 21st international conference on Artificial neural networks - Volume Part II
Training support vector machines via SMO-type decomposition methods
ALT'05 Proceedings of the 16th international conference on Algorithmic Learning Theory
An adaptive support vector machine learning algorithm for large classification problem
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part I
General polynomial time decomposition algorithms
COLT'05 Proceedings of the 18th annual conference on Learning Theory
Fast training of linear programming support vector machines using decomposition techniques
ANNPR'06 Proceedings of the Second international conference on Artificial Neural Networks in Pattern Recognition
Review: Supervised classification and mathematical optimization
Computers and Operations Research
Online learning algorithm of kernel-based ternary classifiers using support vectors
Optical Memory and Neural Networks
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Convergence of a generalized version of the modified SMO algorithms given by Keerthi et al. for SVM classifier design is proved. The convergence results are also extended to modified SMO algorithms for solving ν-SVM classifier problems.