Convergence rates for momentum stochastic gradient descent with noise of machine learning type.
Benjamin GessSebastian KassingPublished in: CoRR (2023)
Keyphrases
- convergence rate
- stochastic gradient descent
- step size
- learning rate
- machine learning
- weight vector
- convergence speed
- number of iterations required
- least squares
- learning algorithm
- random forests
- support vector machine
- machine learning algorithms
- missing data
- noise level
- loss function
- learning problems
- matrix factorization
- machine learning methods
- semi supervised learning
- decision trees
- reinforcement learning
- feature selection
- worst case
- learning models
- markov chain
- model selection
- kernel methods