Stochastic expectation maximization with variance reduction
Expectation-Maximization (EM) is a popular tool for learning latent variable models, but the vanilla batch EM does not scale to large data sets because the whole data set is needed at every E-step. Stochastic Expectation Maximization (sEM) reduces the cost of E-step by stochastic approximation. Howe...
Үндсэн зохиолчид: | Chen, J, Zhu, J, Teh, Y, Zhang, T |
---|---|
Формат: | Conference item |
Хэвлэсэн: |
Massachusetts Institute of Technology Press
2018
|
Ижил төстэй зүйлс
Ижил төстэй зүйлс
-
Non-negative variance component estimation for the partial EIV model by the expectation maximization algorithm
-н: Leyang Wang, зэрэг
Хэвлэсэн: (2020-01-01) -
On the pricing of forward-start variance swaps with stochastic volatility and stochastic interest rate
-н: Roslan, Teh Raihana Nazirah
Хэвлэсэн: (2017) -
Pricing variance swaps under stochastic volatility and stochastic interest rate
-н: Cao, Jiling, зэрэг
Хэвлэсэн: (2016) -
Exploration of the (non-)asymptotic bias and variance of stochastic gradient Langevin dynamics
-н: Vollmer, S, зэрэг
Хэвлэсэн: (2016) -
Accelerated Stochastic Variance Reduction Gradient Algorithms for Robust Subspace Clustering
-н: Hongying Liu, зэрэг
Хэвлэсэн: (2024-06-01)