SVM-SMO-SGD: A hybrid-parallel support vector machine algorithm using sequential minimal optimization with stochastic gradient descent.
Gizen MutluÇigdem Inan AciPublished in: Parallel Comput. (2022)
Keyphrases
- sequential minimal optimization
- support vector machine
- stochastic gradient descent
- support vector
- support vector regression
- radial basis function
- support vector machine svm
- quadratic programming
- matrix factorization
- loss function
- feature selection
- kernel methods
- least squares
- kernel function
- svm classifier
- machine learning
- svm solvers
- multi class
- weight vector
- support vectors
- np hard
- hyperplane
- neural network
- learning algorithm
- training data
- random forests
- generalization ability
- step size
- feature vectors
- training set
- dynamic programming
- decision boundary
- closed form
- optimal solution
- importance sampling
- classification accuracy
- svm training
- logistic regression
- expectation maximization