Stochastic gradient descent-based support vector machines training optimization on Big Data and HPC frameworks.
Vibhatha AbeykoonGeoffrey C. FoxMinje KimSaliya EkanayakeSupun KamburugamuveKannan GovindarajanPulasthi WickramasingheNiranda PereraChathura WidanageAhmet UyarGurhan GunduzSelahatin AkkasPublished in: Concurr. Comput. Pract. Exp. (2022)
Keyphrases
- stochastic gradient descent
- big data
- loss function
- support vector
- least squares
- support vector machine
- matrix factorization
- step size
- cloud computing
- random forests
- logistic regression
- data analysis
- linear svm
- svm training
- business intelligence
- data management
- regularization parameter
- big data analytics
- data processing
- data warehousing
- kernel methods
- support vectors
- pairwise
- weight vector
- multiple kernel learning
- cross validation
- knowledge discovery
- social media
- feature selection
- importance sampling
- hyperplane
- svm classifier
- kernel function
- query processing
- knowledge management
- information processing
- association rules
- objective function
- case study
- training examples