Fast Hyperparameter Tuning for Support Vector Machines with Stochastic Gradient Descent.
Marcin OrchelJohan A. K. SuykensPublished in: LOD (2) (2020)
Keyphrases
- stochastic gradient descent
- multiple kernel learning
- least squares
- loss function
- step size
- matrix factorization
- random forests
- support vector machine
- regularization parameter
- gaussian processes
- gaussian process
- hyperparameters
- model selection
- linear combination
- cross validation
- weight vector
- online algorithms
- maximum a posteriori
- importance sampling
- random forest
- feature selection
- parameter settings
- learning problems
- support vector
- incomplete data
- binary classification
- kernel methods
- decision trees