Stochastic Gradient Descent for Gaussian Processes Done Right.
Jihao Andreas LinShreyas PadhyJavier AntoránAustin TrippAlexander TereninCsaba SzepesváriJosé Miguel Hernández-LobatoDavid JanzPublished in: CoRR (2023)
Keyphrases
- gaussian processes
- stochastic gradient descent
- least squares
- loss function
- matrix factorization
- gaussian process
- random forests
- regularization parameter
- support vector machine
- multiple kernel learning
- multi task
- prior knowledge
- hyperparameters
- missing data
- learning problems
- bayesian framework
- similarity measure
- support vector