The nature of statistical learning theory
The nature of statistical learning theory
Machine Learning
Advances in kernel methods: support vector learning
Advances in kernel methods: support vector learning
Fast training of support vector machines using sequential minimal optimization
Advances in kernel methods
A Brief Introduction to Boosting
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Training Support Vector Machines: an Application to Face Detection
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Scaling Kernel-Based Systems to Large Data Sets
Data Mining and Knowledge Discovery
Efficient computations for large least square support vector machine classifiers
Pattern Recognition Letters
Iterative Data Squashing for Boosting Based on a Distribution-Sensitive Distance
PKDD '02 Proceedings of the 6th European Conference on Principles of Data Mining and Knowledge Discovery
Document preprocessing for naive Bayes classification and clustering with mixture of multinomials
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Bit Reduction Support Vector Machine
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
Concept boundary detection for speeding up SVMs
ICML '06 Proceedings of the 23rd international conference on Machine learning
Information Sciences: an International Journal
A Confident Majority Voting Strategy for Parallel and Modular Support Vector Machines
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III
Nonlinear clustering-based support vector machine for large data sets
Optimization Methods & Software - Mathematical programming in data mining and machine learning
Fast support vector machines for continuous data
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on cybernetics and cognitive informatics
A fast SVM training method for very large datasets
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Boosting lite: handling larger datasets and slower base classifiers
MCS'07 Proceedings of the 7th international conference on Multiple classifier systems
Tree Decomposition for Large-Scale SVM Problems
The Journal of Machine Learning Research
Using the leader algorithm with support vector machines for large data sets
ICANN'11 Proceedings of the 21th international conference on Artificial neural networks - Volume Part I
Hi-index | 0.00 |