A quantum extension of SVM-perf for training nonlinear SVMs in almost linear time.
Jonathan AllcockChang-Yu HsiehPublished in: Quantum (2020)
Keyphrases
- support vector
- kernel svms
- support vector machine svm
- linear svm
- svm training
- support vectors
- support vector machine
- training set
- training speed
- training algorithm
- training process
- training support vector machines
- svm classifier
- training examples
- standard svm
- learning machines
- kernel function
- generalization ability
- feature selection
- hyperplane
- multi class
- classification using support vector machines
- knn
- multiclass svm
- early stopping
- training samples
- kernel methods
- high dimension
- training data
- reduced set
- working set selection
- multi class classification
- svm classification
- logistic regression
- feature space
- linear support vector machines
- statistical learning theory
- text classifiers
- training dataset
- binary classification
- text categorization
- supervised learning
- radial basis function
- stochastic gradient descent
- decision function
- support vector machine classifiers
- rbf kernel
- structural svms
- hyper sphere
- text classification tasks
- train a support vector machine
- selected features
- soft margin
- discriminative classifiers
- ls svm
- maximum margin
- object detectors
- classification algorithm
- classification method
- kernel principal component analysis
- sequential minimal optimization
- structured prediction
- active learning
- multiple kernel learning
- feature vectors
- feature extraction