Minimum precision requirements for the SVM-SGD learning algorithm.
Charbel SakrAmeya D. PatilSai ZhangYongjune KimNaresh R. ShanbhagPublished in: ICASSP (2017)
Keyphrases
- learning algorithm
- generalization ability
- training data
- support vector
- support vector machine svm
- classification algorithm
- stochastic gradient descent
- machine learning
- support vector machine
- machine learning algorithms
- maximum margin
- multi class
- svm solvers
- knn
- feature selection
- high precision
- training algorithm
- learning problems
- svm classifier
- kernel methods
- matrix factorization
- generalization error
- training procedure
- rbf network
- multi class classification
- learning machines
- binary classification
- k nearest neighbor
- reinforcement learning
- svm classification
- learning process
- sample complexity
- learning scheme
- classification method
- text categorization
- back propagation
- supervised learning