An Empirical Study of Stochastic Gradient Descent with Structured Covariance Noise.
Yeming WenKevin LukMaxime GazeauGuodong ZhangHarris ChanJimmy BaPublished in: AISTATS (2020)
Keyphrases
- stochastic gradient descent
- least squares
- matrix factorization
- loss function
- step size
- random forests
- missing data
- support vector machine
- noise reduction
- noise level
- weight vector
- importance sampling
- multiple kernel learning
- objective function
- pairwise
- monte carlo
- similarity measure
- regularization parameter
- online algorithms