Convergence of stochastic gradient descent on parameterized sphere with applications to variational Monte Carlo simulation.
Nilin AbrahamsenZhiyan DingGil GoldshlagerLin LinPublished in: CoRR (2023)
Keyphrases
- monte carlo simulation
- stochastic gradient descent
- step size
- monte carlo
- matrix factorization
- least squares
- convergence rate
- importance sampling
- markov chain
- loss function
- random forests
- convergence speed
- image segmentation
- regularization parameter
- multiple kernel learning
- weight vector
- support vector machine
- optical flow
- image restoration
- collaborative filtering
- learning rate
- differential evolution
- machine learning
- cross validation
- similarity measure
- feature selection