Proximal support vector machine classifiers
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
SSVM: A Smooth Support Vector Machine for Classification
Computational Optimization and Applications
Polyhedral separability through successive LP
Journal of Optimization Theory and Applications
The Supervised Network Self-Organizing Map for Classification of Large Data Sets
Applied Intelligence
Efficient SVM Regression Training with SMO
Machine Learning
A Simple Decomposition Method for Support Vector Machines
Machine Learning
Survival-Time Classification of Breast Cancer Patients
Computational Optimization and Applications
A parallel solver for large quadratic programs in training support vector machines
Parallel Computing - Special issue: Parallel computing in numerical optimization
Lagrangian support vector machines
The Journal of Machine Learning Research
Fast and accurate text classification via multiple linear discriminant projections
The VLDB Journal — The International Journal on Very Large Data Bases
A Support Vector Machine with a Hybrid Kernel and Minimal Vapnik-Chervonenkis Dimension
IEEE Transactions on Knowledge and Data Engineering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Training Support Vector Machines Using Gilbert's Algorithm
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
Training ν-Support Vector Classifiers: Theory and Algorithms
Neural Computation
QP Algorithms with Guaranteed Accuracy and Run Time for Support Vector Machines
The Journal of Machine Learning Research
The Interplay of Optimization and Machine Learning Research
The Journal of Machine Learning Research
Efficient Learning of Label Ranking by Soft Projections onto Polyhedra
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
The optimal design of weighted order statistics filters by using support vector machines
EURASIP Journal on Applied Signal Processing
An improved way tomake large-scale SVR learning practical
EURASIP Journal on Applied Signal Processing
Semismooth Newton support vector machine
Pattern Recognition Letters
A convergent decomposition algorithm for support vector machines
Computational Optimization and Applications
A Multi-criteria Convex Quadratic Programming model for credit data analysis
Decision Support Systems
A dual coordinate descent method for large-scale linear SVM
Proceedings of the 25th international conference on Machine learning
Unsupervised and Semi-supervised Lagrangian Support Vector Machines
ICCS '07 Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007
Ultrasound Estimation of Fetal Weight with Fuzzy Support Vector Regression
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III
Simulation of Time Series Prediction Based on Smooth Support Vector Regression
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III
A support vector machine with integer parameters
Neurocomputing
Extractive Support Vector Algorithm on Support Vector Machines for Image Restoration
Fundamenta Informaticae
Study of Double SMO Algorithm Based on Attributes Reduction
ISNN 2009 Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II
An incremental learning algorithm for Lagrangian support vector machines
Pattern Recognition Letters
A novel SVM-based method for moving video objects recognition
VISUAL'07 Proceedings of the 9th international conference on Advances in visual information systems
Successive overrelaxation for support vector regression
RSFDGrC'03 Proceedings of the 9th international conference on Rough sets, fuzzy sets, data mining, and granular computing
Tree-structured learning of multi-class SVMs with triple learning units
ICNC'09 Proceedings of the 5th international conference on Natural computation
A smoothing function for 1-norm support vector machines
ICNC'09 Proceedings of the 5th international conference on Natural computation
Improvements to train support vector machines based on convex set conception
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 1
Training and Testing Low-degree Polynomial Data Mappings via Linear SVM
The Journal of Machine Learning Research
Computational Optimization and Applications
Fuzzy integral to speed up support vector machines training for pattern classification
International Journal of Knowledge-based and Intelligent Engineering Systems
Exploiting separability in large-scale linear support vector machine training
Computational Optimization and Applications
A simplified multi-class support vector machine with reduced dual optimization
Pattern Recognition Letters
Online support vector machines with vectors sieving method
ISNN'05 Proceedings of the Second international conference on Advances in Neural Networks - Volume Part I
A new smooth support vector machine
CIS'05 Proceedings of the 2005 international conference on Computational Intelligence and Security - Volume Part I
A new multi-criteria convex quadratic programming model for credit analysis
ICCS'06 Proceedings of the 6th international conference on Computational Science - Volume Part IV
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
Training support vector machines with multiple equality constraints
ECML'05 Proceedings of the 16th European conference on Machine Learning
Accurate on-line ν-support vector learning
Neural Networks
A new smooth support vector regression based on ε-insensitive logistic loss function
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part I
A polynomial smooth support vector machine for classification
ADMA'05 Proceedings of the First international conference on Advanced Data Mining and Applications
General polynomial time decomposition algorithms
COLT'05 Proceedings of the 18th annual conference on Learning Theory
A fast data preprocessing procedure for support vector regression
IDEAL'06 Proceedings of the 7th international conference on Intelligent Data Engineering and Automated Learning
Extractive Support Vector Algorithm on Support Vector Machines for Image Restoration
Fundamenta Informaticae
A regularization for the projection twin support vector machine
Knowledge-Based Systems
Stochastic coordinate descent methods for regularized smooth and nonsmooth losses
ECML PKDD'12 Proceedings of the 2012 European conference on Machine Learning and Knowledge Discovery in Databases - Volume Part I
Twin support vector machine with Universum data
Neural Networks
Structural twin support vector machine for classification
Knowledge-Based Systems
Fast instance selection for speeding up support vector machines
Knowledge-Based Systems
Stochastic dual coordinate ascent methods for regularized loss
The Journal of Machine Learning Research
SOR based fuzzy k-means clustering algorithm for classification of remotely sensed images
ISNN'13 Proceedings of the 10th international conference on Advances in Neural Networks - Volume Part I
Keyword spotting in unconstrained handwritten Chinese documents using contextual word model
Image and Vision Computing
Nonparallel hyperplane support vector machine for binary classification problems
Information Sciences: an International Journal
Fast classification for large data sets via random selection clustering and Support Vector Machines
Intelligent Data Analysis
| Hi-index | 0.00 |
Successive overrelaxation (SOR) for symmetric linear complementarity problems and quadratic programs is used to train a support vector machine (SVM) for discriminating between the elements of two massive datasets, each with millions of points. Because SOR handles one point at a time, similar to Platt's sequential minimal optimization (SMO) algorithm (1999) which handles two constraints at a time and Joachims' SVMlight (1998) which handles a small number of points at a time, SOR can process very large datasets that need not reside in memory. The algorithm converges linearly to a solution. Encouraging numerical results are presented on datasets with up to 10 000 000 points. Such massive discrimination problems cannot be processed by conventional linear or quadratic programming methods, and to our knowledge have not been solved by other methods. On smaller problems, SOR was faster than SVMlight and comparable or faster than SMO