Convergence Analysis for Training Stochastic Neural Networks via Stochastic Gradient Descent.
Richard ArchibaldFeng BaoYanzhao CaoHui SunPublished in: CoRR (2022)
Keyphrases
- stochastic gradient descent
- convergence analysis
- neural network
- least squares
- step size
- matrix factorization
- loss function
- convergence rate
- random forests
- global convergence
- training process
- support vector machine
- multiple kernel learning
- optimality conditions
- regularization parameter
- weight vector
- machine learning
- machine learning algorithms
- optimal solution
- support vector
- monte carlo
- logistic regression
- approximation methods
- online algorithms
- decision trees
- collaborative filtering